WorldWideScience

Sample records for imaging modalities compression

  1. Radiological Image Compression

    Science.gov (United States)

    Lo, Shih-Chung Benedict

    The movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve, and transmit the volume of digital images. Basic research into image data compression is necessary in order to move from a film-based department to an efficient digital -based department. Digital data compression technology consists of two types of compression technique: error-free and irreversible. Error -free image compression is desired; however, present techniques can only achieve compression ratio of from 1.5:1 to 3:1, depending upon the image characteristics. Irreversible image compression can achieve a much higher compression ratio; however, the image reconstructed from the compressed data shows some difference from the original image. This dissertation studies both error-free and irreversible image compression techniques. In particular, some modified error-free techniques have been tested and the recommended strategies for various radiological images are discussed. A full-frame bit-allocation irreversible compression technique has been derived. A total of 76 images which include CT head and body, and radiographs digitized to 2048 x 2048, 1024 x 1024, and 512 x 512 have been used to test this algorithm. The normalized mean -square-error (NMSE) on the difference image, defined as the difference between the original and the reconstructed image from a given compression ratio, is used as a global measurement on the quality of the reconstructed image. The NMSE's of total of 380 reconstructed and 380 difference images are measured and the results tabulated. Three complex compression methods are also suggested to compress images with special characteristics. Finally, various parameters which would effect the quality of the reconstructed images are discussed. A proposed hardware compression module is given in the last chapter.

  2. Compression for radiological images

    Science.gov (United States)

    Wilson, Dennis L.

    1992-07-01

    The viewing of radiological images has peculiarities that must be taken into account in the design of a compression technique. The images may be manipulated on a workstation to change the contrast, to change the center of the brightness levels that are viewed, and even to invert the images. Because of the possible consequences of losing information in a medical application, bit preserving compression is used for the images used for diagnosis. However, for archiving the images may be compressed to 10 of their original size. A compression technique based on the Discrete Cosine Transform (DCT) takes the viewing factors into account by compressing the changes in the local brightness levels. The compression technique is a variation of the CCITT JPEG compression that suppresses the blocking of the DCT except in areas of very high contrast.

  3. Radiologic image compression -- A review

    International Nuclear Information System (INIS)

    Wong, S.; Huang, H.K.; Zaremba, L.; Gooden, D.

    1995-01-01

    The objective of radiologic image compression is to reduce the data volume of and to achieve a lot bit rate in the digital representation of radiologic images without perceived loss of image quality. However, the demand for transmission bandwidth and storage space in the digital radiology environment, especially picture archiving and communication systems (PACS) and teleradiology, and the proliferating use of various imaging modalities, such as magnetic resonance imaging, computed tomography, ultrasonography, nuclear medicine, computed radiography, and digital subtraction angiography, continue to outstrip the capabilities of existing technologies. The availability of lossy coding techniques for clinical diagnoses further implicates many complex legal and regulatory issues. This paper reviews the recent progress of lossless and lossy radiologic image compression and presents the legal challenges of using lossy compression of medical records. To do so, the authors first describe the fundamental concepts of radiologic imaging and digitization. Then, the authors examine current compression technology in the field of medical imaging and discuss important regulatory policies and legal questions facing the use of compression in this field. The authors conclude with a summary of future challenges and research directions. 170 refs

  4. Special imaging modalities

    International Nuclear Information System (INIS)

    Torres, W.E.; Fajman, W.A.

    1987-01-01

    Continual advances in technology have made a wide variety of techniques available for diagnostic imaging. The physician caring for the critically ill patient is, therefore, confronted not only with a choice of different procedures, but also frequently with a choice of imaging modalites. Relatively few of these procedures can be performed at the bedside. Consultation between the radiologist and referring physician is necessary not only for choosing the optimum procedure to answer a specific question, but also for expediting movement of the patient with life-support apparatus through a busy radiology department. It is of utmost importance that there be a coordinated effort when a critically ill patient is to be sent to the radiology department; nursing staff and support personnel should be available to accompany the patient to an area where nursing care is generally not available

  5. Image compression of bone images

    International Nuclear Information System (INIS)

    Hayrapetian, A.; Kangarloo, H.; Chan, K.K.; Ho, B.; Huang, H.K.

    1989-01-01

    This paper reports a receiver operating characteristic (ROC) experiment conducted to compare the diagnostic performance of a compressed bone image with the original. The compression was done on custom hardware that implements an algorithm based on full-frame cosine transform. The compression ratio in this study is approximately 10:1, which was decided after a pilot experiment. The image set consisted of 45 hand images, including normal images and images containing osteomalacia and osteitis fibrosa. Each image was digitized with a laser film scanner to 2,048 x 2,048 x 8 bits. Six observers, all board-certified radiologists, participated in the experiment. For each ROC session, an independent ROC curve was constructed and the area under that curve calculated. The image set was randomized for each session, as was the order for viewing the original and reconstructed images. Analysis of variance was used to analyze the data and derive statistically significant results. The preliminary results indicate that the diagnostic quality of the reconstructed image is comparable to that of the original image

  6. Compressive Transient Imaging

    KAUST Repository

    Sun, Qilin

    2017-04-01

    High resolution transient/3D imaging technology is of high interest in both scientific research and commercial application. Nowadays, all of the transient imaging methods suffer from low resolution or time consuming mechanical scanning. We proposed a new method based on TCSPC and Compressive Sensing to achieve a high resolution transient imaging with a several seconds capturing process. Picosecond laser sends a serious of equal interval pulse while synchronized SPAD camera\\'s detecting gate window has a precise phase delay at each cycle. After capturing enough points, we are able to make up a whole signal. By inserting a DMD device into the system, we are able to modulate all the frames of data using binary random patterns to reconstruct a super resolution transient/3D image later. Because the low fill factor of SPAD sensor will make a compressive sensing scenario ill-conditioned, We designed and fabricated a diffractive microlens array. We proposed a new CS reconstruction algorithm which is able to denoise at the same time for the measurements suffering from Poisson noise. Instead of a single SPAD senor, we chose a SPAD array because it can drastically reduce the requirement for the number of measurements and its reconstruction time. Further more, it not easy to reconstruct a high resolution image with only one single sensor while for an array, it just needs to reconstruct small patches and a few measurements. In this thesis, we evaluated the reconstruction methods using both clean measurements and the version corrupted by Poisson noise. The results show how the integration over the layers influence the image quality and our algorithm works well while the measurements suffer from non-trival Poisson noise. It\\'s a breakthrough in the areas of both transient imaging and compressive sensing.

  7. Compressive sensing in medical imaging.

    Science.gov (United States)

    Graff, Christian G; Sidky, Emil Y

    2015-03-10

    The promise of compressive sensing, exploitation of compressibility to achieve high quality image reconstructions with less data, has attracted a great deal of attention in the medical imaging community. At the Compressed Sensing Incubator meeting held in April 2014 at OSA Headquarters in Washington, DC, presentations were given summarizing some of the research efforts ongoing in compressive sensing for x-ray computed tomography and magnetic resonance imaging systems. This article provides an expanded version of these presentations. Sparsity-exploiting reconstruction algorithms that have gained popularity in the medical imaging community are studied, and examples of clinical applications that could benefit from compressive sensing ideas are provided. The current and potential future impact of compressive sensing on the medical imaging field is discussed.

  8. Image quality (IQ) guided multispectral image compression

    Science.gov (United States)

    Zheng, Yufeng; Chen, Genshe; Wang, Zhonghai; Blasch, Erik

    2016-05-01

    Image compression is necessary for data transportation, which saves both transferring time and storage space. In this paper, we focus on our discussion on lossy compression. There are many standard image formats and corresponding compression algorithms, for examples, JPEG (DCT -- discrete cosine transform), JPEG 2000 (DWT -- discrete wavelet transform), BPG (better portable graphics) and TIFF (LZW -- Lempel-Ziv-Welch). The image quality (IQ) of decompressed image will be measured by numerical metrics such as root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural Similarity (SSIM) Index. Given an image and a specified IQ, we will investigate how to select a compression method and its parameters to achieve an expected compression. Our scenario consists of 3 steps. The first step is to compress a set of interested images by varying parameters and compute their IQs for each compression method. The second step is to create several regression models per compression method after analyzing the IQ-measurement versus compression-parameter from a number of compressed images. The third step is to compress the given image with the specified IQ using the selected compression method (JPEG, JPEG2000, BPG, or TIFF) according to the regressed models. The IQ may be specified by a compression ratio (e.g., 100), then we will select the compression method of the highest IQ (SSIM, or PSNR). Or the IQ may be specified by a IQ metric (e.g., SSIM = 0.8, or PSNR = 50), then we will select the compression method of the highest compression ratio. Our experiments tested on thermal (long-wave infrared) images (in gray scales) showed very promising results.

  9. Mammography image compression using Wavelet

    International Nuclear Information System (INIS)

    Azuhar Ripin; Md Saion Salikin; Wan Hazlinda Ismail; Asmaliza Hashim; Norriza Md Isa

    2004-01-01

    Image compression plays an important role in many applications like medical imaging, televideo conferencing, remote sensing, document and facsimile transmission, which depend on the efficient manipulation, storage, and transmission of binary, gray scale, or color images. In Medical imaging application such Picture Archiving and Communication System (PACs), the image size or image stream size is too large and requires a large amount of storage space or high bandwidth for communication. Image compression techniques are divided into two categories namely lossy and lossless data compression. Wavelet method used in this project is a lossless compression method. In this method, the exact original mammography image data can be recovered. In this project, mammography images are digitized by using Vider Sierra Plus digitizer. The digitized images are compressed by using this wavelet image compression technique. Interactive Data Language (IDLs) numerical and visualization software is used to perform all of the calculations, to generate and display all of the compressed images. Results of this project are presented in this paper. (Author)

  10. Performance evaluation of breast image compression techniques

    Energy Technology Data Exchange (ETDEWEB)

    Anastassopoulos, G; Lymberopoulos, D [Wire Communications Laboratory, Electrical Engineering Department, University of Patras, Greece (Greece); Panayiotakis, G; Bezerianos, A [Medical Physics Department, School of Medicine, University of Patras, Greece (Greece)

    1994-12-31

    Novel diagnosis orienting tele working systems manipulate, store, and process medical data through real time communication - conferencing schemes. One of the most important factors affecting the performance of these systems is image handling. Compression algorithms can be applied to the medical images, in order to minimize : a) the volume of data to be stored in the database, b) the demanded bandwidth from the network, c) the transmission costs, and to minimize the speed of the transmitted data. In this paper an estimation of all the factors of the process that affect the presentation of breast images is made, from the time the images are produced from a modality, till the compressed images are stored, or transmitted in a Broadband network (e.g. B-ISDN). The images used were scanned images of the TOR(MAX) Leeds breast phantom, as well as typical breast images. A comparison of seven compression techniques has been done, based on objective criteria such as Mean Square Error (MSE), resolution, contrast, etc. The user can choose the appropriate compression ratio in order to achieve the desired image quality. (authors). 12 refs, 4 figs.

  11. Performance evaluation of breast image compression techniques

    International Nuclear Information System (INIS)

    Anastassopoulos, G.; Lymberopoulos, D.; Panayiotakis, G.; Bezerianos, A.

    1994-01-01

    Novel diagnosis orienting tele working systems manipulate, store, and process medical data through real time communication - conferencing schemes. One of the most important factors affecting the performance of these systems is image handling. Compression algorithms can be applied to the medical images, in order to minimize : a) the volume of data to be stored in the database, b) the demanded bandwidth from the network, c) the transmission costs, and to minimize the speed of the transmitted data. In this paper an estimation of all the factors of the process that affect the presentation of breast images is made, from the time the images are produced from a modality, till the compressed images are stored, or transmitted in a Broadband network (e.g. B-ISDN). The images used were scanned images of the TOR(MAX) Leeds breast phantom, as well as typical breast images. A comparison of seven compression techniques has been done, based on objective criteria such as Mean Square Error (MSE), resolution, contrast, etc. The user can choose the appropriate compression ratio in order to achieve the desired image quality. (authors)

  12. Images compression in nuclear medicine

    International Nuclear Information System (INIS)

    Rebelo, M.S.; Furuie, S.S.; Moura, L.

    1992-01-01

    The performance of two methods for images compression in nuclear medicine was evaluated. The LZW precise, and Cosine Transformed, approximate, methods were analyzed. The results were obtained, showing that the utilization of approximated method produced images with an agreeable quality for visual analysis and compression rates, considerably high than precise method. (C.G.C.)

  13. Perceptual Image Compression in Telemedicine

    Science.gov (United States)

    Watson, Andrew B.; Ahumada, Albert J., Jr.; Eckstein, Miguel; Null, Cynthia H. (Technical Monitor)

    1996-01-01

    The next era of space exploration, especially the "Mission to Planet Earth" will generate immense quantities of image data. For example, the Earth Observing System (EOS) is expected to generate in excess of one terabyte/day. NASA confronts a major technical challenge in managing this great flow of imagery: in collection, pre-processing, transmission to earth, archiving, and distribution to scientists at remote locations. Expected requirements in most of these areas clearly exceed current technology. Part of the solution to this problem lies in efficient image compression techniques. For much of this imagery, the ultimate consumer is the human eye. In this case image compression should be designed to match the visual capacities of the human observer. We have developed three techniques for optimizing image compression for the human viewer. The first consists of a formula, developed jointly with IBM and based on psychophysical measurements, that computes a DCT quantization matrix for any specified combination of viewing distance, display resolution, and display brightness. This DCT quantization matrix is used in most recent standards for digital image compression (JPEG, MPEG, CCITT H.261). The second technique optimizes the DCT quantization matrix for each individual image, based on the contents of the image. This is accomplished by means of a model of visual sensitivity to compression artifacts. The third technique extends the first two techniques to the realm of wavelet compression. Together these two techniques will allow systematic perceptual optimization of image compression in NASA imaging systems. Many of the image management challenges faced by NASA are mirrored in the field of telemedicine. Here too there are severe demands for transmission and archiving of large image databases, and the imagery is ultimately used primarily by human observers, such as radiologists. In this presentation I will describe some of our preliminary explorations of the applications

  14. Compression of Infrared images

    DEFF Research Database (Denmark)

    Mantel, Claire; Forchhammer, Søren

    2017-01-01

    best for bits-per-pixel rates below 1.4 bpp, while HEVC obtains best performance in the range 1.4 to 6.5 bpp. The compression performance is also evaluated based on maximum errors. These results also show that HEVC can achieve a precision of 1°C with an average of 1.3 bpp....

  15. Double-compression method for biomedical images

    Science.gov (United States)

    Antonenko, Yevhenii A.; Mustetsov, Timofey N.; Hamdi, Rami R.; Małecka-Massalska, Teresa; Orshubekov, Nurbek; DzierŻak, RóŻa; Uvaysova, Svetlana

    2017-08-01

    This paper describes a double compression method (DCM) of biomedical images. A comparison of image compression factors in size JPEG, PNG and developed DCM was carried out. The main purpose of the DCM - compression of medical images while maintaining the key points that carry diagnostic information. To estimate the minimum compression factor an analysis of the coding of random noise image is presented.

  16. Established rheumatoid arthritis - new imaging modalities

    DEFF Research Database (Denmark)

    McQueen, Fiona M; Østergaard, Mikkel

    2007-01-01

    New imaging modalities are assuming an increasingly important role in the investigation and management of rheumatoid arthritis. It is now possible to obtain information about all tissues within the joint in three dimensions using tomographic techniques such as magnetic resonance imaging (MRI...

  17. Established rheumatoid arthritis - new imaging modalities

    DEFF Research Database (Denmark)

    McQueen, Fiona M; Østergaard, Mikkel

    2007-01-01

    in real-time and facilitates diagnostic and therapeutic interventions such as joint aspiration and injection. Exciting experimental modalities are also being developed with the potential to provide not just morphological but functional imaging. Techniques such as positron emission tomography (PET......) and high-resolution computerized tomography. Erosions are very clearly depicted using these modalities and MRI also allows imaging of soft tissues with assessment of joint inflammation. High-resolution ultrasound is a convenient clinical technique for the assessment of erosions, synovitis and tenosynovitis...

  18. Compressive Transient Imaging

    KAUST Repository

    Sun, Qilin

    2017-01-01

    measurements and the version corrupted by Poisson noise. The results show how the integration over the layers influence the image quality and our algorithm works well while the measurements suffer from non-trival Poisson noise. It's a breakthrough in the areas

  19. Diagnostic imaging of compression neuropathy

    International Nuclear Information System (INIS)

    Weishaupt, D.; Andreisek, G.

    2007-01-01

    Compression-induced neuropathy of peripheral nerves can cause severe pain of the foot and ankle. Early diagnosis is important to institute prompt treatment and to minimize potential injury. Although clinical examination combined with electrophysiological studies remain the cornerstone of the diagnostic work-up, in certain cases, imaging may provide key information with regard to the exact anatomic location of the lesion or aid in narrowing the differential diagnosis. In other patients with peripheral neuropathies of the foot and ankle, imaging may establish the etiology of the condition and provide information crucial for management and/or surgical planning. MR imaging and ultrasound provide direct visualization of the nerve and surrounding abnormalities. Bony abnormalities contributing to nerve compression are best assessed by radiographs and CT. Knowledge of the anatomy, the etiology, typical clinical findings, and imaging features of peripheral neuropathies affecting the peripheral nerves of the foot and ankle will allow for a more confident diagnosis. (orig.) [de

  20. [Medical image compression: a review].

    Science.gov (United States)

    Noreña, Tatiana; Romero, Eduardo

    2013-01-01

    Modern medicine is an increasingly complex activity , based on the evidence ; it consists of information from multiple sources : medical record text , sound recordings , images and videos generated by a large number of devices . Medical imaging is one of the most important sources of information since they offer comprehensive support of medical procedures for diagnosis and follow-up . However , the amount of information generated by image capturing gadgets quickly exceeds storage availability in radiology services , generating additional costs in devices with greater storage capacity . Besides , the current trend of developing applications in cloud computing has limitations, even though virtual storage is available from anywhere, connections are made through internet . In these scenarios the optimal use of information necessarily requires powerful compression algorithms adapted to medical activity needs . In this paper we present a review of compression techniques used for image storage , and a critical analysis of them from the point of view of their use in clinical settings.

  1. Evaluation of a new image compression technique

    International Nuclear Information System (INIS)

    Algra, P.R.; Kroon, H.M.; Noordveld, R.B.; DeValk, J.P.J.; Seeley, G.W.; Westerink, P.H.

    1988-01-01

    The authors present the evaluation of a new image compression technique, subband coding using vector quantization, on 44 CT examinations of the upper abdomen. Three independent radiologists reviewed the original images and compressed versions. The compression ratios used were 16:1 and 20:1. Receiver operating characteristic analysis showed no difference in the diagnostic contents between originals and their compressed versions. Subjective visibility of anatomic structures was equal. Except for a few 20:1 compressed images, the observers could not distinguish compressed versions from original images. They conclude that subband coding using vector quantization is a valuable method for data compression in CT scans of the abdomen

  2. Efficient Lossy Compression for Compressive Sensing Acquisition of Images in Compressive Sensing Imaging Systems

    Directory of Open Access Journals (Sweden)

    Xiangwei Li

    2014-12-01

    Full Text Available Compressive Sensing Imaging (CSI is a new framework for image acquisition, which enables the simultaneous acquisition and compression of a scene. Since the characteristics of Compressive Sensing (CS acquisition are very different from traditional image acquisition, the general image compression solution may not work well. In this paper, we propose an efficient lossy compression solution for CS acquisition of images by considering the distinctive features of the CSI. First, we design an adaptive compressive sensing acquisition method for images according to the sampling rate, which could achieve better CS reconstruction quality for the acquired image. Second, we develop a universal quantization for the obtained CS measurements from CS acquisition without knowing any a priori information about the captured image. Finally, we apply these two methods in the CSI system for efficient lossy compression of CS acquisition. Simulation results demonstrate that the proposed solution improves the rate-distortion performance by 0.4~2 dB comparing with current state-of-the-art, while maintaining a low computational complexity.

  3. The task of control digital image compression

    OpenAIRE

    TASHMANOV E.B.; МАМАTOV М.S.

    2014-01-01

    In this paper we consider the relationship of control tasks and image compression losses. The main idea of this approach is to allocate structural lines simplified image and further compress the selected data

  4. Imaging Breast Density: Established and Emerging Modalities

    Directory of Open Access Journals (Sweden)

    Jeon-Hor Chen

    2015-12-01

    Full Text Available Mammographic density has been proven as an independent risk factor for breast cancer. Women with dense breast tissue visible on a mammogram have a much higher cancer risk than women with little density. A great research effort has been devoted to incorporate breast density into risk prediction models to better estimate each individual’s cancer risk. In recent years, the passage of breast density notification legislation in many states in USA requires that every mammography report should provide information regarding the patient’s breast density. Accurate definition and measurement of breast density are thus important, which may allow all the potential clinical applications of breast density to be implemented. Because the two-dimensional mammography-based measurement is subject to tissue overlapping and thus not able to provide volumetric information, there is an urgent need to develop reliable quantitative measurements of breast density. Various new imaging technologies are being developed. Among these new modalities, volumetric mammographic density methods and three-dimensional magnetic resonance imaging are the most well studied. Besides, emerging modalities, including different x-ray–based, optical imaging, and ultrasound-based methods, have also been investigated. All these modalities may either overcome some fundamental problems related to mammographic density or provide additional density and/or compositional information. The present review article aimed to summarize the current established and emerging imaging techniques for the measurement of breast density and the evidence of the clinical use of these density methods from the literature.

  5. JPEG and wavelet compression of ophthalmic images

    Science.gov (United States)

    Eikelboom, Robert H.; Yogesan, Kanagasingam; Constable, Ian J.; Barry, Christopher J.

    1999-05-01

    This study was designed to determine the degree and methods of digital image compression to produce ophthalmic imags of sufficient quality for transmission and diagnosis. The photographs of 15 subjects, which inclined eyes with normal, subtle and distinct pathologies, were digitized to produce 1.54MB images and compressed to five different methods: (i) objectively by calculating the RMS error between the uncompressed and compressed images, (ii) semi-subjectively by assessing the visibility of blood vessels, and (iii) subjectively by asking a number of experienced observers to assess the images for quality and clinical interpretation. Results showed that as a function of compressed image size, wavelet compressed images produced less RMS error than JPEG compressed images. Blood vessel branching could be observed to a greater extent after Wavelet compression compared to JPEG compression produced better images then a JPEG compression for a given image size. Overall, it was shown that images had to be compressed to below 2.5 percent for JPEG and 1.7 percent for Wavelet compression before fine detail was lost, or when image quality was too poor to make a reliable diagnosis.

  6. Subjective evaluation of compressed image quality

    Science.gov (United States)

    Lee, Heesub; Rowberg, Alan H.; Frank, Mark S.; Choi, Hyung-Sik; Kim, Yongmin

    1992-05-01

    Lossy data compression generates distortion or error on the reconstructed image and the distortion becomes visible as the compression ratio increases. Even at the same compression ratio, the distortion appears differently depending on the compression method used. Because of the nonlinearity of the human visual system and lossy data compression methods, we have evaluated subjectively the quality of medical images compressed with two different methods, an intraframe and interframe coding algorithms. The evaluated raw data were analyzed statistically to measure interrater reliability and reliability of an individual reader. Also, the analysis of variance was used to identify which compression method is better statistically, and from what compression ratio the quality of a compressed image is evaluated as poorer than that of the original. Nine x-ray CT head images from three patients were used as test cases. Six radiologists participated in reading the 99 images (some were duplicates) compressed at four different compression ratios, original, 5:1, 10:1, and 15:1. The six readers agree more than by chance alone and their agreement was statistically significant, but there were large variations among readers as well as within a reader. The displacement estimated interframe coding algorithm is significantly better in quality than that of the 2-D block DCT at significance level 0.05. Also, 10:1 compressed images with the interframe coding algorithm do not show any significant differences from the original at level 0.05.

  7. Lossless Compression of Digital Images

    DEFF Research Database (Denmark)

    Martins, Bo

    Presently, tree coders are the best bi-level image coders. The currentISO standard, JBIG, is a good example.By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code.A number of general-purpose coders...... version that is substantially faster than its precursorsand brings it close to the multi-pass coders in compression performance.Handprinted characters are of unequal complexity; recent work by Singer and Tishby demonstrates that utilizing the physiological process of writing one can synthesize cursive.......The feature vector of a bitmap initially constitutes a lossy representation of the contour(s) of the bitmap. The initial feature space is usually too large but can be reduced automatically by use ofa predictive code length or predictive error criterion....

  8. Mathematical transforms and image compression: A review

    Directory of Open Access Journals (Sweden)

    Satish K. Singh

    2010-07-01

    Full Text Available It is well known that images, often used in a variety of computer and other scientific and engineering applications, are difficult to store and transmit due to their sizes. One possible solution to overcome this problem is to use an efficient digital image compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. All the contemporary digital image compression systems use various mathematical transforms for compression. The compression performance is closely related to the performance by these mathematical transforms in terms of energy compaction and spatial frequency isolation by exploiting inter-pixel redundancies present in the image data. Through this paper, a comprehensive literature survey has been carried out and the pros and cons of various transform-based image compression models have also been discussed.

  9. Combined Sparsifying Transforms for Compressive Image Fusion

    Directory of Open Access Journals (Sweden)

    ZHAO, L.

    2013-11-01

    Full Text Available In this paper, we present a new compressive image fusion method based on combined sparsifying transforms. First, the framework of compressive image fusion is introduced briefly. Then, combined sparsifying transforms are presented to enhance the sparsity of images. Finally, a reconstruction algorithm based on the nonlinear conjugate gradient is presented to get the fused image. The simulations demonstrate that by using the combined sparsifying transforms better results can be achieved in terms of both the subjective visual effect and the objective evaluation indexes than using only a single sparsifying transform for compressive image fusion.

  10. Wavelets: Applications to Image Compression-II

    Indian Academy of Sciences (India)

    Wavelets: Applications to Image Compression-II. Sachin P ... successful application of wavelets in image com- ... b) Soft threshold: In this case, all the coefficients x ..... [8] http://www.jpeg.org} Official site of the Joint Photographic Experts Group.

  11. MR imaging of medullary compression due to vertebral metastases

    International Nuclear Information System (INIS)

    Dooms, G.C.; Mathurin, P.; Maldague, B.; Cornelis, G.; Malghem, J.; Demeure, R.

    1987-01-01

    A prospective study was performed to assess the value of MR imaging for demonstrating medullary compression due to vertebral metastases in cancer patients clinically suspected of presenting with that complication. Twenty-five consecutive unselected patients were studied, and the MR imaging findings were confirmed by myelography, CT, and/or surgical and autopsy findings for each patient. The MR examinations were performed with a superconducting magnet (Philips Gyroscan S15) operating at 0.5-T. MR imaging demonstrated the metastases (single or multiple) mainly on T1- weighted images (TR = 0.45 sec and TE = 20 msec). Soft-tissue tumoral mass and/or deformity of a vertebral body secondary to metastasis, compressing the spinal cord, was equally demonstrated on T1- and heavily T2-weighted images (TR = 1.65 sec and TE = 100 msec). In the sagittal plane, MR imaging demonstrated the exact level of the compression (one or multiple levels) and its full extent. In conclusion, MR is the first imaging modality for studying cancer patients with clinically suspected medullary compression and obviates the need for more invasive procedures

  12. Multimodal Image Alignment via Linear Mapping between Feature Modalities.

    Science.gov (United States)

    Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

    2017-01-01

    We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

  13. Compression and archiving of digital images

    International Nuclear Information System (INIS)

    Huang, H.K.

    1988-01-01

    This paper describes the application of a full-frame bit-allocation image compression technique to a hierarchical digital image archiving system consisting of magnetic disks, optical disks and an optical disk library. The digital archiving system without the compression has been in clinical operation in the Pediatric Radiology for more than half a year. The database in the system consists of all pediatric inpatients including all images from computed radiography, digitized x-ray films, CT, MR, and US. The rate of image accumulation is approximately 1,900 megabytes per week. The hardware design of the compression module is based on a Motorola 68020 microprocessor, A VME bus, a 16 megabyte image buffer memory board, and three Motorola digital signal processing 56001 chips on a VME board for performing the two-dimensional cosine transform and the quantization. The clinical evaluation of the compression module with the image archiving system is expected to be in February 1988

  14. Imaging modalities of abdominal tumors in children

    International Nuclear Information System (INIS)

    Reither, M.

    1993-01-01

    Further technological progress in cross-sectional imaging modalities, accumuting experience with increasingly refined hardware and software and accumulating specific contrast media allow new algorithms for the assessment of abdominal tumors in children. However, ultrasound remains the diagnostic method of choice: Conventional roentgenology with or without contrast media is decreasing, but often reveals further differential diagnostic details. MRI is becoming more prominent and is often performed immediately after ultrasound. The inauguration of gradient echo sequences and consequent shorter examination times combined with the elimination of pulsation and motion artefacts extends the diagnostic spectrum of the upper and middle abdomen. The application of oral or rectal contrast agents for imaging of the GI tract ameliorates the differentiation of pathologic processes. Recently volumetric CT/ultrafast CT has been gaining in importance for abdominal examinations in the pediatric age group. CT especially is helpful if there are bony structures in the region being examined. CT, however, involves ionizing radiation and timely administration of oral and intravenous contrast material. Moreover, as pediatric radiologists, we must strongly withstand tendencies to perform CT more often because it is less expensive, rather than avoiding ionizing radiation by using MRI. (orig.) [de

  15. Composite Techniques Based Color Image Compression

    Directory of Open Access Journals (Sweden)

    Zainab Ibrahim Abood

    2017-03-01

    Full Text Available Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S, composite wavelet technique (W and composite multi-wavelet technique (M. For the high energy sub-band of the 3rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM in M technique which has the highest values of energy (En and compression ratio (CR and least values of bit per pixel (bpp, time (T and rate distortion R(D. Also the values of the compression parameters of the color image are nearly the same as the average values of the compression parameters of the three bands of the same image.

  16. Data compression of digital X-ray images from a clinical viewpoint

    International Nuclear Information System (INIS)

    Ando, Yutaka

    1992-01-01

    For the PACS (picture archiving and communication system), large storage capacity recording media and a fast data transfer network are necessary. When the PACS are working, these technology requirements become an large problem. So we need image data compression having a higher recording efficiency media and an improved transmission ratio. There are two kinds of data compression methods, one is reversible compression and other is the irreversible one. By these reversible compression methods, a compressed-expanded image is exactly equal to the original image. The ratio of data compression is about between 1/2 an d1/3. On the other hand, for irreversible data compression, the compressed-expanded image is a distorted image, and we can achieve a high compression ratio by using this method. In the medical field, the discrete cosine transform (DCT) method is popular because of the low distortion and fast performance. The ratio of data compression is actually from 1/10 to 1/20. It is important for us to decide the compression ratio according to the purposes and modality of the image. We must carefully select the ratio of the data compression because the suitable compression ratio alters in the usage of image for education, clinical diagnosis and reference. (author)

  17. Image data compression in diagnostic imaging. International literature review and workflow recommendation

    International Nuclear Information System (INIS)

    Braunschweig, R.; Kaden, Ingmar; Schwarzer, J.; Sprengel, C.; Klose, K.

    2009-01-01

    Purpose: Today healthcare policy is based on effectiveness. Diagnostic imaging became a ''pace-setter'' due to amazing technical developments (e.g. multislice CT), extensive data volumes, and especially the well defined workflow-orientated scenarios on a local and (inter)national level. To make centralized networks sufficient, image data compression has been regarded as the key to a simple and secure solution. In February 2008 specialized working groups of the DRG held a consensus conference. They designed recommended data compression techniques and ratios. Material und methoden: The purpose of our paper is an international review of the literature of compression technologies, different imaging procedures (e.g. DR, CT etc.), and targets (abdomen, etc.) and to combine recommendations for compression ratios and techniques with different workflows. The studies were assigned to 4 different levels (0-3) according to the evidence. 51 studies were assigned to the highest level 3. Results: We recommend a compression factor of 1: 8 (excluding cranial scans 1:5). For workflow reasons data compression should be based on the modalities (CT, etc.). PACS-based compression is currently possible but fails to maximize workflow benefits. Only the modality-based scenarios achieve all benefits. (orig.)

  18. Image data compression in diagnostic imaging. International literature review and workflow recommendation

    Energy Technology Data Exchange (ETDEWEB)

    Braunschweig, R.; Kaden, Ingmar [Klinik fuer Bildgebende Diagnostik und Interventionsradiologie, BG-Kliniken Bergmannstrost Halle (Germany); Schwarzer, J.; Sprengel, C. [Dept. of Management Information System and Operations Research, Martin-Luther-Univ. Halle Wittenberg (Germany); Klose, K. [Medizinisches Zentrum fuer Radiologie, Philips-Univ. Marburg (Germany)

    2009-07-15

    Purpose: Today healthcare policy is based on effectiveness. Diagnostic imaging became a ''pace-setter'' due to amazing technical developments (e.g. multislice CT), extensive data volumes, and especially the well defined workflow-orientated scenarios on a local and (inter)national level. To make centralized networks sufficient, image data compression has been regarded as the key to a simple and secure solution. In February 2008 specialized working groups of the DRG held a consensus conference. They designed recommended data compression techniques and ratios. Material und methoden: The purpose of our paper is an international review of the literature of compression technologies, different imaging procedures (e.g. DR, CT etc.), and targets (abdomen, etc.) and to combine recommendations for compression ratios and techniques with different workflows. The studies were assigned to 4 different levels (0-3) according to the evidence. 51 studies were assigned to the highest level 3. Results: We recommend a compression factor of 1: 8 (excluding cranial scans 1:5). For workflow reasons data compression should be based on the modalities (CT, etc.). PACS-based compression is currently possible but fails to maximize workflow benefits. Only the modality-based scenarios achieve all benefits. (orig.)

  19. Image and Dose Simulation in Support of New Imaging Modalities

    International Nuclear Information System (INIS)

    Kuruvilla Verghese

    2002-01-01

    This report summarizes the highlights of the research performed under the 2-year NEER grant from the Department of Energy. The primary outcome of the work was a new Monte Carlo code, MCMIS-DS, for Monte Carlo for Mammography Image Simulation including Differential Sampling. The code was written to generate simulated images and dose distributions from two different new digital x-ray imaging modalities, namely, synchrotron imaging (SI) and a slot geometry digital mammography system called Fisher Senoscan. A differential sampling scheme was added to the code to generate multiple images that included variations in the parameters of the measurement system and the object in a single execution of the code. The code is to serve multiple purposes; (1) to answer questions regarding the contribution of scattered photons to images, (2) for use in design optimization studies, and (3) to do up to second-order perturbation studies to assess the effects of design parameter variations and/or physical parameters of the object (the breast) without having to re-run the code for each set of varied parameters. The accuracy and fidelity of the code were validated by a large variety of benchmark studies using published data and also using experimental results from mammography phantoms on both imaging modalities

  20. Context-Aware Image Compression.

    Directory of Open Access Journals (Sweden)

    Jacky C K Chan

    Full Text Available We describe a physics-based data compression method inspired by the photonic time stretch wherein information-rich portions of the data are dilated in a process that emulates the effect of group velocity dispersion on temporal signals. With this coding operation, the data can be downsampled at a lower rate than without it. In contrast to previous implementation of the warped stretch compression, here the decoding can be performed without the need of phase recovery. We present rate-distortion analysis and show improvement in PSNR compared to compression via uniform downsampling.

  1. Cloud Optimized Image Format and Compression

    Science.gov (United States)

    Becker, P.; Plesea, L.; Maurer, T.

    2015-04-01

    Cloud based image storage and processing requires revaluation of formats and processing methods. For the true value of the massive volumes of earth observation data to be realized, the image data needs to be accessible from the cloud. Traditional file formats such as TIF and NITF were developed in the hay day of the desktop and assumed fast low latency file access. Other formats such as JPEG2000 provide for streaming protocols for pixel data, but still require a server to have file access. These concepts no longer truly hold in cloud based elastic storage and computation environments. This paper will provide details of a newly evolving image storage format (MRF) and compression that is optimized for cloud environments. Although the cost of storage continues to fall for large data volumes, there is still significant value in compression. For imagery data to be used in analysis and exploit the extended dynamic range of the new sensors, lossless or controlled lossy compression is of high value. Compression decreases the data volumes stored and reduces the data transferred, but the reduced data size must be balanced with the CPU required to decompress. The paper also outlines a new compression algorithm (LERC) for imagery and elevation data that optimizes this balance. Advantages of the compression include its simple to implement algorithm that enables it to be efficiently accessed using JavaScript. Combing this new cloud based image storage format and compression will help resolve some of the challenges of big image data on the internet.

  2. Iris Recognition: The Consequences of Image Compression

    Directory of Open Access Journals (Sweden)

    Bishop DanielA

    2010-01-01

    Full Text Available Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

  3. Iris Recognition: The Consequences of Image Compression

    Science.gov (United States)

    Ives, Robert W.; Bishop, Daniel A.; Du, Yingzi; Belcher, Craig

    2010-12-01

    Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

  4. High-quality compressive ghost imaging

    Science.gov (United States)

    Huang, Heyan; Zhou, Cheng; Tian, Tian; Liu, Dongqi; Song, Lijun

    2018-04-01

    We propose a high-quality compressive ghost imaging method based on projected Landweber regularization and guided filter, which effectively reduce the undersampling noise and improve the resolution. In our scheme, the original object is reconstructed by decomposing of regularization and denoising steps instead of solving a minimization problem in compressive reconstruction process. The simulation and experimental results show that our method can obtain high ghost imaging quality in terms of PSNR and visual observation.

  5. A New Approach for Fingerprint Image Compression

    Energy Technology Data Exchange (ETDEWEB)

    Mazieres, Bertrand

    1997-12-01

    The FBI has been collecting fingerprint cards since 1924 and now has over 200 million of them. Digitized with 8 bits of grayscale resolution at 500 dots per inch, it means 2000 terabytes of information. Also, without any compression, transmitting a 10 Mb card over a 9600 baud connection will need 3 hours. Hence we need a compression and a compression as close to lossless as possible: all fingerprint details must be kept. A lossless compression usually do not give a better compression ratio than 2:1, which is not sufficient. Compressing these images with the JPEG standard leads to artefacts which appear even at low compression rates. Therefore the FBI has chosen in 1993 a scheme of compression based on a wavelet transform, followed by a scalar quantization and an entropy coding : the so-called WSQ. This scheme allows to achieve compression ratios of 20:1 without any perceptible loss of quality. The publication of the FBI specifies a decoder, which means that many parameters can be changed in the encoding process: the type of analysis/reconstruction filters, the way the bit allocation is made, the number of Huffman tables used for the entropy coding. The first encoder used 9/7 filters for the wavelet transform and did the bit allocation using a high-rate bit assumption. Since the transform is made into 64 subbands, quite a lot of bands receive only a few bits even at an archival quality compression rate of 0.75 bit/pixel. Thus, after a brief overview of the standard, we will discuss a new approach for the bit-allocation that seems to make more sense where theory is concerned. Then we will talk about some implementation aspects, particularly for the new entropy coder and the features that allow other applications than fingerprint image compression. Finally, we will compare the performances of the new encoder to those of the first encoder.

  6. Image splitting and remapping method for radiological image compression

    Science.gov (United States)

    Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

    1990-07-01

    A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

  7. Multiband and Lossless Compression of Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Raffaele Pizzolante

    2016-02-01

    Full Text Available Hyperspectral images are widely used in several real-life applications. In this paper, we investigate on the compression of hyperspectral images by considering different aspects, including the optimization of the computational complexity in order to allow implementations on limited hardware (i.e., hyperspectral sensors, etc.. We present an approach that relies on a three-dimensional predictive structure. Our predictive structure, 3D-MBLP, uses one or more previous bands as references to exploit the redundancies among the third dimension. The achieved results are comparable, and often better, with respect to the other state-of-art lossless compression techniques for hyperspectral images.

  8. HVS-based medical image compression

    Energy Technology Data Exchange (ETDEWEB)

    Kai Xie [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)]. E-mail: xie_kai2001@sjtu.edu.cn; Jie Yang [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China); Min Zhuyue [CREATIS-CNRS Research Unit 5515 and INSERM Unit 630, 69621 Villeurbanne (France); Liang Lixiao [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)

    2005-07-01

    Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time.

  9. HVS-based medical image compression

    International Nuclear Information System (INIS)

    Kai Xie; Jie Yang; Min Zhuyue; Liang Lixiao

    2005-01-01

    Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time

  10. Efficient predictive algorithms for image compression

    CERN Document Server

    Rosário Lucas, Luís Filipe; Maciel de Faria, Sérgio Manuel; Morais Rodrigues, Nuno Miguel; Liberal Pagliari, Carla

    2017-01-01

    This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is in...

  11. Imaging Modalities for Cervical Spondylotic Stenosis and Myelopathy

    Directory of Open Access Journals (Sweden)

    C. Green

    2012-01-01

    Full Text Available Cervical spondylosis is a spectrum of pathology presenting as neck pain, radiculopathy, and myelopathy or all in combination. Diagnostic imaging is essential to diagnosis and preoperative planning. We discuss the modalities of imaging in common practice. We examine the use of imaging to differentiate among central, subarticular, and lateral stenosis and in the assessment of myelopathy.

  12. High-speed reconstruction of compressed images

    Science.gov (United States)

    Cox, Jerome R., Jr.; Moore, Stephen M.

    1990-07-01

    A compression scheme is described that allows high-definition radiological images with greater than 8-bit intensity resolution to be represented by 8-bit pixels. Reconstruction of the images with their original intensity resolution can be carried out by means of a pipeline architecture suitable for compact, high-speed implementation. A reconstruction system is described that can be fabricated according to this approach and placed between an 8-bit display buffer and the display's video system thereby allowing contrast control of images at video rates. Results for 50 CR chest images are described showing that error-free reconstruction of the original 10-bit CR images can be achieved.

  13. Diagnostic Approach in Impotence and Imaging Modalities

    Directory of Open Access Journals (Sweden)

    Medih Celiktas

    2015-06-01

    Full Text Available Penile erection results from a complex interplay between central nerveus system and local factors. Several aspects of these interactions have been the subject of many reviews. Nocturnal penile tumescence (NPT monitoring is the best single non-invasive examination to differentiate organic from psychogenic impotence. Angiography and pharmaco-cevernosometry are accepted as gold standard modalities in the assesment of vasculojenic impotence. Recently color Doppler sonography made the detection of vessels easier and the correction of the Doppler angle more accurate, resulting in more rapid and accurate acquisition of data. [Cukurova Med J 2015; 40(2.000: 208-211

  14. Dictionary Approaches to Image Compression and Reconstruction

    Science.gov (United States)

    Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

    1998-01-01

    This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.

  15. Lossy image compression for digital medical imaging systems

    Science.gov (United States)

    Wilhelm, Paul S.; Haynor, David R.; Kim, Yongmin; Nelson, Alan C.; Riskin, Eve A.

    1990-07-01

    Image compression at rates of 10:1 or greater could make PACS much more responsive and economically attractive. This paper describes a protocol for subjective and objective evaluation of the fidelity of compressed/decompressed images to the originals and presents the results ofits application to four representative and promising compression methods. The methods examined are predictive pruned tree-structured vector quantization, fractal compression, the discrete cosine transform with equal weighting of block bit allocation, and the discrete cosine transform with human visual system weighting of block bit allocation. Vector quantization is theoretically capable of producing the best compressed images, but has proven to be difficult to effectively implement. It has the advantage that it can reconstruct images quickly through a simple lookup table. Disadvantages are that codebook training is required, the method is computationally intensive, and achieving the optimum performance would require prohibitively long vector dimensions. Fractal compression is a relatively new compression technique, but has produced satisfactory results while being computationally simple. It is fast at both image compression and image reconstruction. Discrete cosine iransform techniques reproduce images well, but have traditionally been hampered by the need for intensive computing to compress and decompress images. A protocol was developed for side-by-side observer comparison of reconstructed images with originals. Three 1024 X 1024 CR (Computed Radiography) images and two 512 X 512 X-ray CT images were viewed at six bit rates (0.2, 0.4, 0.6, 0.9, 1.2, and 1.5 bpp for CR, and 1.0, 1.3, 1.6, 1.9, 2.2, 2.5 bpp for X-ray CT) by nine radiologists at the University of Washington Medical Center. The CR images were viewed on a Pixar II Megascan (2560 X 2048) monitor and the CT images on a Sony (1280 X 1024) monitor. The radiologists' subjective evaluations of image fidelity were compared to

  16. Optical cell sorting with multiple imaging modalities

    DEFF Research Database (Denmark)

    Banas, Andrew; Carrissemoux, Caro; Palima, Darwin

    2017-01-01

    healthy cells. With the richness of visual information, a lot of microscopy techniques have been developed and have been crucial in biological studies. To utilize their complementary advantages we adopt both fluorescence and brightfield imaging in our optical cell sorter. Brightfield imaging has...... the advantage of being non-invasive, thus maintaining cell viability. Fluorescence imaging, on the other hand, takes advantages of the chemical specificity of fluorescence markers and can validate machine vision results from brightfield images. Visually identified cells are sorted using optical manipulation...

  17. ROI-based DICOM image compression for telemedicine

    Indian Academy of Sciences (India)

    ground and reconstruct the image portions losslessly. The compressed image can ... If the image is compressed by 8:1 compression without any perceptual distortion, the ... Figure 2. Cross-sectional view of medical image (statistical representation). ... The Integer Wavelet Transform (IWT) is used to have lossless processing.

  18. Multi-Modality Registration And Fusion Of Medical Image Data

    International Nuclear Information System (INIS)

    Kassak, P.; Vencko, D.; Cerovsky, I.

    2008-01-01

    Digitalisation of health care providing facilities allows US to maximize the usage of digital data from one patient obtained by various modalities. Complex view on to the problem can be achieved from the site of morphology as well as functionality. Multi-modal registration and fusion of medical image data is one of the examples that provides improved insight and allows more precise approach and treatment. (author)

  19. Image compression with Iris-C

    Science.gov (United States)

    Gains, David

    2009-05-01

    Iris-C is an image codec designed for streaming video applications that demand low bit rate, low latency, lossless image compression. To achieve compression and low latency the codec features the discrete wavelet transform, Exp-Golomb coding, and online processes that construct dynamic models of the input video. Like H.264 and Dirac, the Iris-C codec accepts input video from both the YUV and YCOCG colour spaces, but the system can also operate on Bayer RAW data read directly from an image sensor. Testing shows that the Iris-C codec is competitive with the Dirac low delay syntax codec which is typically regarded as the state-of-the-art low latency, lossless video compressor.

  20. Autonomy of image and use of single or multiple sense modalities in original verbal image production.

    Science.gov (United States)

    Khatena, J

    1978-06-01

    The use of a single or of multiple sense modalities in the production of original verbal images as related to autonomy of imagery was explored. 72 college adults were administered Onomatopoeia and Images and the Gordon Test of Visual Imagery Control. A modified scoring procedure for the Gordon scale differentiated imagers who were moderate or low in autonomy. The two groups produced original verbal images using multiple sense modalities more frequently than a single modality.

  1. Diffusion tensor imaging in spinal cord compression

    International Nuclear Information System (INIS)

    Wang, Wei; Qin, Wen; Hao, Nanxin; Wang, Yibin; Zong, Genlin

    2012-01-01

    Background Although diffusion tensor imaging has been successfully applied in brain research for decades, several main difficulties have hindered its extended utilization in spinal cord imaging. Purpose To assess the feasibility and clinical value of diffusion tensor imaging and tractography for evaluating chronic spinal cord compression. Material and Methods Single-shot spin-echo echo-planar DT sequences were scanned in 42 spinal cord compression patients and 49 healthy volunteers. The mean values of the apparent diffusion coefficient and fractional anisotropy were measured in region of interest at the cervical and lower thoracic spinal cord. The patients were divided into two groups according to the high signal on T2WI (the SCC-HI group and the SCC-nHI group for with or without high signal). A one-way ANOVA was used. Diffusion tensor tractography was used to visualize the morphological features of normal and impaired white matter. Results There were no statistically significant differences in the apparent diffusion coefficient and fractional anisotropy values between the different spinal cord segments of the normal subjects. All of the patients in the SCC-HI group had increased apparent diffusion coefficient values and decreased fractional anisotropy values at the lesion level compared to the normal controls. However, there were no statistically significant diffusion index differences between the SCC-nHI group and the normal controls. In the diffusion tensor imaging maps, the normal spinal cord sections were depicted as fiber tracts that were color-encoded to a cephalocaudal orientation. The diffusion tensor images were compressed to different degrees in all of the patients. Conclusion Diffusion tensor imaging and tractography are promising methods for visualizing spinal cord tracts and can provide additional information in clinical studies in spinal cord compression

  2. Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

    Science.gov (United States)

    Liu, Dong; Wang, Dandan; Li, Houqiang

    2017-12-01

    Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

  3. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  4. Three-dimensional imaging modalities in endodontics

    Science.gov (United States)

    Mao, Teresa

    2014-01-01

    Recent research in endodontics has highlighted the need for three-dimensional imaging in the clinical arena as well as in research. Three-dimensional imaging using computed tomography (CT) has been used in endodontics over the past decade. Three types of CT scans have been studied in endodontics, namely cone-beam CT, spiral CT, and peripheral quantitative CT. Contemporary endodontics places an emphasis on the use of cone-beam CT for an accurate diagnosis of parameters that cannot be visualized on a two-dimensional image. This review discusses the role of CT in endodontics, pertaining to its importance in the diagnosis of root canal anatomy, detection of peri-radicular lesions, diagnosis of trauma and resorption, presurgical assessment, and evaluation of the treatment outcome. PMID:25279337

  5. Three-dimensional imaging modalities in endodontics

    Energy Technology Data Exchange (ETDEWEB)

    Mao, Teresa; Neelakantan, Prasanna [Dept. of Conservative Dentistry and Endodontics, Saveetha Dental College and Hospitals, Saveetha University, Chennai (India)

    2014-09-15

    Recent research in endodontics has highlighted the need for three-dimensional imaging in the clinical arena as well as in research. Three-dimensional imaging using computed tomography (CT) has been used in endodontics over the past decade. Three types of CT scans have been studied in endodontics, namely cone-beam CT, spiral CT, and peripheral quantitative CT. Contemporary endodontics places an emphasis on the use of cone-beam CT for an accurate diagnosis of parameters that cannot be visualized on a two-dimensional image. This review discusses the role of CT in endodontics, pertaining to its importance in the diagnosis of root canal anatomy, detection of peri-radicular lesions, diagnosis of trauma and resorption, presurgical assessment, and evaluation of the treatment outcome.

  6. Three-dimensional imaging modalities in endodontics

    International Nuclear Information System (INIS)

    Mao, Teresa; Neelakantan, Prasanna

    2014-01-01

    Recent research in endodontics has highlighted the need for three-dimensional imaging in the clinical arena as well as in research. Three-dimensional imaging using computed tomography (CT) has been used in endodontics over the past decade. Three types of CT scans have been studied in endodontics, namely cone-beam CT, spiral CT, and peripheral quantitative CT. Contemporary endodontics places an emphasis on the use of cone-beam CT for an accurate diagnosis of parameters that cannot be visualized on a two-dimensional image. This review discusses the role of CT in endodontics, pertaining to its importance in the diagnosis of root canal anatomy, detection of peri-radicular lesions, diagnosis of trauma and resorption, presurgical assessment, and evaluation of the treatment outcome

  7. Expandable image compression system: A modular approach

    International Nuclear Information System (INIS)

    Ho, B.K.T.; Lo, S.C.; Huang, H.K.

    1986-01-01

    The full-frame bit-allocation algorithm for radiological image compression can achieve an acceptable compression ratio as high as 30:1. It involves two stages of operation: a two-dimensional discrete cosine transform and pixel quantization in the transformed space with pixel depth kept accountable by a bit-allocation table. The cosine transform hardware design took an expandable modular approach based on the VME bus system with a maximum data transfer rate of 48 Mbytes/sec and a microprocessor (Motorola 68000 family). The modules are cascadable and microprogrammable to perform 1,024-point butterfly operations. A total of 18 stages would be required for transforming a 1,000 x 1,000 image. Multiplicative constants and addressing sequences are to be software loaded into the parameter buffers of each stage prior to streaming data through the processor stages. The compression rate for 1K x 1K images is expected to be faster than one image per sec

  8. Compressive sensing based ptychography image encryption

    Science.gov (United States)

    Rawat, Nitin

    2015-09-01

    A compressive sensing (CS) based ptychography combined with an optical image encryption is proposed. The diffraction pattern is recorded through ptychography technique further compressed by non-uniform sampling via CS framework. The system requires much less encrypted data and provides high security. The diffraction pattern as well as the lesser measurements of the encrypted samples serves as a secret key which make the intruder attacks more difficult. Furthermore, CS shows that the linearly projected few random samples have adequate information for decryption with a dramatic volume reduction. Experimental results validate the feasibility and effectiveness of our proposed technique compared with the existing techniques. The retrieved images do not reveal any information with the original information. In addition, the proposed system can be robust even with partial encryption and under brute-force attacks.

  9. Modality

    DEFF Research Database (Denmark)

    Klinge, Alex; Müller, Henrik Høeg

    Modality: Studies in Form and Function reflects the diversity of theoretical frameworks and the heterogeneity of linguistic phenomena under the general heading of modality. Researchers in the fields of logic, philosophy and linguistics have for many years been pondering the elusive nature...... of modality and grappled with ways of capturing it. The 11 studies included here cover the span from contributions that seek to clarify controversial theoretical constructs to studies which take an empirical approach to linguistic categories and cross-linguistic typological issues. The key concepts addressed...

  10. Compression of the digitized X-ray images

    International Nuclear Information System (INIS)

    Terae, Satoshi; Miyasaka, Kazuo; Fujita, Nobuyuki; Takamura, Akio; Irie, Goro; Inamura, Kiyonari.

    1987-01-01

    Medical images are using an increased amount of space in the hospitals, while they are not accessed easily. Thus, suitable data filing system and precise data compression will be necessitated. Image quality was evaluated before and after image data compression, using local filing system (MediFile 1000, NEC Co.) and forty-seven modes of compression parameter. For this study X-ray images of 10 plain radiographs and 7 contrast examinations were digitized using a film reader of CCD sensor in MediFile 1000. Those images were compressed into forty-seven kinds of image data to save in an optical disc and then the compressed images were reconstructed. Each reconstructed image was compared with non-compressed images in respect to several regions of our interest by four radiologists. Compression and extension of radiological images were promptly made by employing the local filing system. Image quality was much more affected by the ratio of data compression than by the mode of parameter itself. In another word, the higher compression ratio became, the worse the image quality were. However, image quality was not significantly degraded until the compression ratio was about 15: 1 on plain radiographs and about 8: 1 on contrast studies. Image compression by this technique will be admitted by diagnostic radiology. (author)

  11. Task-oriented lossy compression of magnetic resonance images

    Science.gov (United States)

    Anderson, Mark C.; Atkins, M. Stella; Vaisey, Jacques

    1996-04-01

    A new task-oriented image quality metric is used to quantify the effects of distortion introduced into magnetic resonance images by lossy compression. This metric measures the similarity between a radiologist's manual segmentation of pathological features in the original images and the automated segmentations performed on the original and compressed images. The images are compressed using a general wavelet-based lossy image compression technique, embedded zerotree coding, and segmented using a three-dimensional stochastic model-based tissue segmentation algorithm. The performance of the compression system is then enhanced by compressing different regions of the image volume at different bit rates, guided by prior knowledge about the location of important anatomical regions in the image. Application of the new system to magnetic resonance images is shown to produce compression results superior to the conventional methods, both subjectively and with respect to the segmentation similarity metric.

  12. Image Segmentation, Registration, Compression, and Matching

    Science.gov (United States)

    Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

    2011-01-01

    A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity

  13. Reconfigurable Hardware for Compressing Hyperspectral Image Data

    Science.gov (United States)

    Aranki, Nazeeh; Namkung, Jeffrey; Villapando, Carlos; Kiely, Aaron; Klimesh, Matthew; Xie, Hua

    2010-01-01

    High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of

  14. Musculoskeletal ultrasound and other imaging modalities in rheumatoid arthritis.

    Science.gov (United States)

    Ohrndorf, Sarah; Werner, Stephanie G; Finzel, Stephanie; Backhaus, Marina

    2013-05-01

    This review refers to the use of musculoskeletal ultrasound in patients with rheumatoid arthritis (RA) both in clinical practice and research. Furthermore, other novel sensitive imaging modalities (high resolution peripheral quantitative computed tomography and fluorescence optical imaging) are introduced in this article. Recently published ultrasound studies presented power Doppler activity by ultrasound highly predictive for later radiographic erosions in patients with RA. Another study presented synovitis detected by ultrasound being predictive of subsequent structural radiographic destruction irrespective of the ultrasound modality (grayscale ultrasound/power Doppler ultrasound). Further studies are currently under way which prove ultrasound findings as imaging biomarkers in the destructive process of RA. Other introduced novel imaging modalities are in the validation process to prove their impact and significance in inflammatory joint diseases. The introduced imaging modalities show different sensitivities and specificities as well as strength and weakness belonging to the assessment of inflammation, differentiation of the involved structures and radiological progression. The review tries to give an answer regarding how to best integrate them into daily clinical practice with the aim to improve the diagnostic algorithms, the daily patient care and, furthermore, the disease's outcome.

  15. Implementation and applications of dual-modality imaging

    Science.gov (United States)

    Hasegawa, Bruce H.; Barber, William C.; Funk, Tobias; Hwang, Andrew B.; Taylor, Carmen; Sun, Mingshan; Seo, Youngho

    2004-06-01

    In medical diagnosis, functional or physiological data can be acquired using radionuclide imaging with positron emission tomography or with single-photon emission computed tomography. However, anatomical or structural data can be acquired using X-ray computed tomography. In dual-modality imaging, both radionuclide and X-ray detectors are incorporated in an imaging system to allow both functional and structural data to be acquired in a single procedure without removing the patient from the imaging system. In a clinical setting, dual-modality imaging systems commonly are used to localize radiopharmaceutical uptake with respect to the patient's anatomy. This helps the clinician to differentiate disease from regions of normal radiopharmaceutical accumulation, to improve diagnosis or cancer staging, or to facilitate planning for radiation therapy or surgery. While initial applications of dual-modality imaging were developed for clinical imaging on humans, it now is recognized that these systems have potentially important applications for imaging small animals involved in experimental studies including basic investigations of mammalian biology and development of new pharmaceuticals for diagnosis or treatment of disease.

  16. CMOS Compressed Imaging by Random Convolution

    OpenAIRE

    Jacques, Laurent; Vandergheynst, Pierre; Bibet, Alexandre; Majidzadeh, Vahid; Schmid, Alexandre; Leblebici, Yusuf

    2009-01-01

    We present a CMOS imager with built-in capability to perform Compressed Sensing. The adopted sensing strategy is the random Convolution due to J. Romberg. It is achieved by a shift register set in a pseudo-random configuration. It acts as a convolutive filter on the imager focal plane, the current issued from each CMOS pixel undergoing a pseudo-random redirection controlled by each component of the filter sequence. A pseudo-random triggering of the ADC reading is finally applied to comp...

  17. Automatic intra-modality brain image registration method

    International Nuclear Information System (INIS)

    Whitaker, J.M.; Ardekani, B.A.; Braun, M.

    1996-01-01

    Full text: Registration of 3D images of brain of the same or different subjects has potential importance in clinical diagnosis, treatment planning and neurological research. The broad aim of our work is to produce an automatic and robust intra-modality, brain image registration algorithm for intra-subject and inter-subject studies. Our algorithm is composed of two stages. Initial alignment is achieved by finding the values of nine transformation parameters (representing translation, rotation and scale) that minimise the nonoverlapping regions of the head. This is achieved by minimisation of the sum of the exclusive OR of two binary head images, produced using the head extraction procedure described by Ardekani et al. (J Comput Assist Tomogr, 19:613-623, 1995). The initial alignment successfully determines the scale parameters and gross translation and rotation parameters. Fine alignment uses an objective function described for inter-modality registration in Ardekani et al. (ibid.). The algorithm segments one of the images to be aligned into a set of connected components using K-means clustering. Registration is achieved by minimising the K-means variance of the segmentation induced in the other image. Similarity of images of the same modality makes the method attractive for intra-modality registration. A 3D MR image, with voxel dimensions, 2x2x6 mm, was misaligned. The registered image shows visually accurate registration. The average displacement of a pixel from its correct location was measured to be 3.3 mm. The algorithm was tested on intra-subject MR images and was found to produce good qualitative results. Using the data available, the algorithm produced promising qualitative results in intra-subject registration. Further work is necessary in its application to intersubject registration, due to large variability in brain structure between subjects. Clinical evaluation of the algorithm for selected applications is required

  18. An efficient adaptive arithmetic coding image compression technology

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Yun Jiao-Jiao; Zhang Yong-Lei

    2011-01-01

    This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures the quality of the decoded image combined with the adaptive probability model and predictive coding. The use of adaptive models for each encoded image block dynamically estimates the probability of the relevant image block. The decoded image block can accurately recover the encoded image according to the code book information. We adopt an adaptive arithmetic coding algorithm for image compression that greatly improves the image compression rate. The results show that it is an effective compression technology. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  19. Correspondence normalized ghost imaging on compressive sensing

    International Nuclear Information System (INIS)

    Zhao Sheng-Mei; Zhuang Peng

    2014-01-01

    Ghost imaging (GI) offers great potential with respect to conventional imaging techniques. It is an open problem in GI systems that a long acquisition time is be required for reconstructing images with good visibility and signal-to-noise ratios (SNRs). In this paper, we propose a new scheme to get good performance with a shorter construction time. We call it correspondence normalized ghost imaging based on compressive sensing (CCNGI). In the scheme, we enhance the signal-to-noise performance by normalizing the reference beam intensity to eliminate the noise caused by laser power fluctuations, and reduce the reconstruction time by using both compressive sensing (CS) and time-correspondence imaging (CI) techniques. It is shown that the qualities of the images have been improved and the reconstruction time has been reduced using CCNGI scheme. For the two-grayscale ''double-slit'' image, the mean square error (MSE) by GI and the normalized GI (NGI) schemes with the measurement number of 5000 are 0.237 and 0.164, respectively, and that is 0.021 by CCNGI scheme with 2500 measurements. For the eight-grayscale ''lena'' object, the peak signal-to-noise rates (PSNRs) are 10.506 and 13.098, respectively using GI and NGI schemes while the value turns to 16.198 using CCNGI scheme. The results also show that a high-fidelity GI reconstruction has been achieved using only 44% of the number of measurements corresponding to the Nyquist limit for the two-grayscale “double-slit'' object. The qualities of the reconstructed images using CCNGI are almost the same as those from GI via sparsity constraints (GISC) with a shorter reconstruction time. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  20. Expandable image compression system: A modular approach

    International Nuclear Information System (INIS)

    Ho, B.K.T.; Chan, K.K.; Ishimitsu, Y.; Lo, S.C.; Huang, H.K.

    1987-01-01

    The full-frame bit allocation algorithm for radiological image compression developed in the authors' laboratory can achieve compression ratios as high as 30:1. The software development and clinical evaluation of this algorithm has been completed. It involves two stages of operations: a two-dimensional discrete cosine transform and pixel quantization in the transform space with pixel depth kept accountable by a bit allocation table. Their design took an expandable modular approach based on the VME bus system which has a maximum data transfer rate of 48 Mbytes per second and a Motorola 68020 microprocessor as the master controller. The transform modules are based on advanced digital signal processor (DSP) chips microprogrammed to perform fast cosine transforms. Four DSP's built into a single-board transform module can process an 1K x 1K image in 1.7 seconds. Additional transform modules working in parallel can be added if even greater speeds are desired. The flexibility inherent in the microcode extends the capabilities of the system to incorporate images of variable sizes. Their design allows for a maximum image size of 2K x 2K

  1. Imaging of congenital heart disease in adults: choice of modalities.

    Science.gov (United States)

    Orwat, Stefan; Diller, Gerhard-Paul; Baumgartner, Helmut

    2014-01-01

    Major advances in noninvasive imaging of adult congenital heart disease have been accomplished. These tools play now a key role in comprehensive diagnostic work-up, decision for intervention, evaluation for the suitability of specific therapeutic options, monitoring of interventions and regular follow-up. Besides echocardiography, magnetic resonance (CMR) and computed tomography (CT) have gained particular importance. The choice of imaging modality has thus become a critical issue. This review summarizes strengths and limitations of the different imaging modalities and how they may be used in a complementary fashion. Echocardiography obviously remains the workhorse of imaging routinely used in all patients. However, in complex disease and after surgery echocardiography alone frequently remains insufficient. CMR is particularly useful in this setting and allows reproducible and accurate quantification of ventricular function and comprehensive assessment of cardiac anatomy, aorta, pulmonary arteries and venous return including complex flow measurements. CT is preferred when CMR is contraindicated, when superior spatial resolution is required or when "metallic" artefacts limit CMR imaging. In conclusion, the use of currently available imaging modalities in adult congenital heart disease needs to be complementary. Echocardiography remains the basis tool, CMR and CT should be added considering specific open questions and the ability to answer them, availability and economic issues.

  2. Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images

    Energy Technology Data Exchange (ETDEWEB)

    Shih, Tzu-Ching [Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, 40402, Taiwan (China); Chen, Jeon-Hor; Nie Ke; Lin Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying [Tu and Yuen Center for Functional Onco-Imaging and Radiological Sciences, University of California, Irvine, CA 92697 (United States); Liu Dongxu; Sun Lizhi, E-mail: shih@mail.cmu.edu.t [Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697 (United States)

    2010-07-21

    This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo (registered) 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc (registered) software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under

  3. Multi-modality molecular imaging: pre-clinical laboratory configuration

    Science.gov (United States)

    Wu, Yanjun; Wellen, Jeremy W.; Sarkar, Susanta K.

    2006-02-01

    In recent years, the prevalence of in vivo molecular imaging applications has rapidly increased. Here we report on the construction of a multi-modality imaging facility in a pharmaceutical setting that is expected to further advance existing capabilities for in vivo imaging of drug distribution and the interaction with their target. The imaging instrumentation in our facility includes a microPET scanner, a four wavelength time-domain optical imaging scanner, a 9.4T/30cm MRI scanner and a SPECT/X-ray CT scanner. An electronics shop and a computer room dedicated to image analysis are additional features of the facility. The layout of the facility was designed with a central animal preparation room surrounded by separate laboratory rooms for each of the major imaging modalities to accommodate the work-flow of simultaneous in vivo imaging experiments. This report will focus on the design of and anticipated applications for our microPET and optical imaging laboratory spaces. Additionally, we will discuss efforts to maximize the daily throughput of animal scans through development of efficient experimental work-flows and the use of multiple animals in a single scanning session.

  4. Application of content-based image compression to telepathology

    Science.gov (United States)

    Varga, Margaret J.; Ducksbury, Paul G.; Callagy, Grace

    2002-05-01

    Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content. None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

  5. Data compression of scanned halftone images

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Jensen, Kim S.

    1994-01-01

    with the halftone grid, and converted to a gray level representation. A new digital description of (halftone) grids has been developed for this purpose. The gray level values are coded according to a scheme based on states derived from a segmentation of gray values. To enable real-time processing of high resolution...... scanner output, the coding has been parallelized and implemented on a transputer system. For comparison, the test image was coded using existing (lossless) methods giving compression rates of 2-7. The best of these, a combination of predictive and binary arithmetic coding was modified and optimized...

  6. SU-E-I-53: Variation in Measurements of Breast Skin Thickness Obtained Using Different Imaging Modalities

    International Nuclear Information System (INIS)

    Nguyen, U; Kumaraswamy, N; Markey, M

    2014-01-01

    Purpose: To investigate variation in measurements of breast skin thickness obtained using different imaging modalities, including mammography, computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI). Methods: Breast skin thicknesses as measured by mammography, CT, ultrasound, and MRI were compared. Mammographic measurements of skin thickness were obtained from published studies that utilized standard positioning (upright) and compression. CT measurements of skin thickness were obtained from a published study of a prototype breast CT scanner in which the women were in the prone position and the breast was uncompressed. Dermatological ultrasound exams of the breast skin were conducted at our institution, with the subjects in the upright position and the breast uncompressed. Breast skin thickness was calculated from breast MRI exams at our institution, with the patient in the prone position and the breast uncompressed. Results: T tests for independent samples demonstrated significant differences in the mean breast skin thickness as measured by different imaging modalities. Repeated measures ANOVA revealed significant differences in breast skin thickness across different quadrants of the breast for some modalities. Conclusion: The measurement of breast skin thickness is significantly different across different imaging modalities. Differences in the amount of compression and differences in patient positioning are possible reasons why measurements of breast skin thickness vary by modality

  7. A new hyperspectral image compression paradigm based on fusion

    Science.gov (United States)

    Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

    2016-10-01

    The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

  8. Watermark Compression in Medical Image Watermarking Using Lempel-Ziv-Welch (LZW) Lossless Compression Technique.

    Science.gov (United States)

    Badshah, Gran; Liew, Siau-Chuin; Zain, Jasni Mohd; Ali, Mushtaq

    2016-04-01

    In teleradiology, image contents may be altered due to noisy communication channels and hacker manipulation. Medical image data is very sensitive and can not tolerate any illegal change. Illegally changed image-based analysis could result in wrong medical decision. Digital watermarking technique can be used to authenticate images and detect as well as recover illegal changes made to teleradiology images. Watermarking of medical images with heavy payload watermarks causes image perceptual degradation. The image perceptual degradation directly affects medical diagnosis. To maintain the image perceptual and diagnostic qualities standard during watermarking, the watermark should be lossless compressed. This paper focuses on watermarking of ultrasound medical images with Lempel-Ziv-Welch (LZW) lossless-compressed watermarks. The watermark lossless compression reduces watermark payload without data loss. In this research work, watermark is the combination of defined region of interest (ROI) and image watermarking secret key. The performance of the LZW compression technique was compared with other conventional compression methods based on compression ratio. LZW was found better and used for watermark lossless compression in ultrasound medical images watermarking. Tabulated results show the watermark bits reduction, image watermarking with effective tamper detection and lossless recovery.

  9. On-board image compression for the RAE lunar mission

    Science.gov (United States)

    Miller, W. H.; Lynch, T. J.

    1976-01-01

    The requirements, design, implementation, and flight performance of an on-board image compression system for the lunar orbiting Radio Astronomy Explorer-2 (RAE-2) spacecraft are described. The image to be compressed is a panoramic camera view of the long radio astronomy antenna booms used for gravity-gradient stabilization of the spacecraft. A compression ratio of 32 to 1 is obtained by a combination of scan line skipping and adaptive run-length coding. The compressed imagery data are convolutionally encoded for error protection. This image compression system occupies about 1000 cu cm and consumes 0.4 W.

  10. Comparison of imaging modalities for diagnosis of thyroid disorders

    International Nuclear Information System (INIS)

    Pfannenstiel, P.; Hirsch, H.; Stein, N.; Maier, R.; Meindl, S.; Voges, K.; Willmann, L.

    1984-01-01

    From 4-1-1980 to 3-30-1983 in more than 10000 patients scanning of the thyroid was performed by a rectiliniear scanner and predominantly by a gamma-camera using a special collimator and a data processing unit for evaluation of global and regional uptake of sup(99m)TcO 4 or 123 I. The functional scans were compared with the structural information provided by real-time ultrasonography of the thyroid, employing in questionable cases specially developed computer aided pattern recognition methods. Other modalities as a multiwire camera, X-ray fluorescence, CT-imaging, NMR-tomography were also evaluated in selected cases. From the data a diagnostic strategy for the use of imaging modalities to diagnose thyroid diseases was derived. (orig.) [de

  11. Compressed sensing in imaging mass spectrometry

    International Nuclear Information System (INIS)

    Bartels, Andreas; Dülk, Patrick; Trede, Dennis; Alexandrov, Theodore; Maaß, Peter

    2013-01-01

    Imaging mass spectrometry (IMS) is a technique of analytical chemistry for spatially resolved, label-free and multipurpose analysis of biological samples that is able to detect the spatial distribution of hundreds of molecules in one experiment. The hyperspectral IMS data is typically generated by a mass spectrometer analyzing the surface of the sample. In this paper, we propose a compressed sensing approach to IMS which potentially allows for faster data acquisition by collecting only a part of the pixels in the hyperspectral image and reconstructing the full image from this data. We present an integrative approach to perform both peak-picking spectra and denoising m/z-images simultaneously, whereas the state of the art data analysis methods solve these problems separately. We provide a proof of the robustness of the recovery of both the spectra and individual channels of the hyperspectral image and propose an algorithm to solve our optimization problem which is based on proximal mappings. The paper concludes with the numerical reconstruction results for an IMS dataset of a rat brain coronal section. (paper)

  12. Cardiac Computed Tomography as an Imaging Modality in Coronary Anomalies.

    Science.gov (United States)

    Karliova, Irem; Fries, Peter; Schmidt, Jörg; Schneider, Ulrich; Shalabi, Ahmad; Schäfers, Hans-Joachim

    2018-01-01

    Coronary artery fistulae and coronary aneurysms are rare anomalies. When they become symptomatic, they require precise anatomic information to allow for planning of the therapeutic procedure. We report a case in which both fistulae and aneurysm were present. The required information could only be obtained by electrocardiogram-gated computed tomography with reformation. This imaging modality should be considered in every case of fistula or coronary aneurysm. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  13. Compressed Sensing Techniques Applied to Ultrasonic Imaging of Cargo Containers

    Directory of Open Access Journals (Sweden)

    Yuri Álvarez López

    2017-01-01

    Full Text Available One of the key issues in the fight against the smuggling of goods has been the development of scanners for cargo inspection. X-ray-based radiographic system scanners are the most developed sensing modality. However, they are costly and use bulky sources that emit hazardous, ionizing radiation. Aiming to improve the probability of threat detection, an ultrasonic-based technique, capable of detecting the footprint of metallic containers or compartments concealed within the metallic structure of the inspected cargo, has been proposed. The system consists of an array of acoustic transceivers that is attached to the metallic structure-under-inspection, creating a guided acoustic Lamb wave. Reflections due to discontinuities are detected in the images, provided by an imaging algorithm. Taking into consideration that the majority of those images are sparse, this contribution analyzes the application of Compressed Sensing (CS techniques in order to reduce the amount of measurements needed, thus achieving faster scanning, without compromising the detection capabilities of the system. A parametric study of the image quality, as a function of the samples needed in spatial and frequency domains, is presented, as well as the dependence on the sampling pattern. For this purpose, realistic cargo inspection scenarios have been simulated.

  14. Radiological Evaluation of Ambiguous Genitalia with Various Imaging Modalities

    Science.gov (United States)

    Ravi, N.; Bindushree, Kadakola

    2012-07-01

    Disorders of sex development (DSDs) are congenital conditions in which the development of chromosomal, gonadal, or anatomic sex is atypical. These can be classified broadly into four categories on the basis of gonadal histologic features: female pseudohermaphroditism (46,XX with two ovaries); male pseudohermaphroditism (46,XY with two testes); true hermaphroditism (ovotesticular DSD) (both ovarian and testicular tissues); and gonadal dysgenesis, either mixed (a testis and a streak gonad) or pure (bilateral streak gonads). Imaging plays an important role in demonstrating the anatomy and associated anomalies. Ultrasonography is the primary modality for demonstrating internal organs and magnetic resonance imaging is used as an adjunct modality to assess for internal gonads and genitalia. Early and appropriate gender assignment is necessary for healthy physical and psychologic development of children with ambiguous genitalia. Gender assignment can be facilitated with a team approach that involves a pediatric endocrinologist, geneticist, urologist, psychiatrist, social worker, neonatologist, nurse, and radiologist, allowing timely diagnosis and proper management. We describe case series on ambiguous genitalia presented to our department who were evaluated with multiple imaging modalities.

  15. The research progress of dual-modality probes for molecular imaging

    International Nuclear Information System (INIS)

    Cao Feng; Chen Yue

    2010-01-01

    Various imaging modalities have been exploited to investigate the anatomic or functional dissemination of tissues in the body. However, no single imaging modality allows overall structural, functional, and molecular information as each imaging modality has its own unique strengths and weaknesses. The combination of two imaging modalities that investigates the strengths of different methods might offer the prospect of improved diagnostic abilities. As more and more dual-modality imaging system have become clinically adopted, significant progress has been made toward the creation of dual-modality imaging probes, which can be used as novel tools for future multimodality systems. These all-in-one probes take full advantage of two different imaging modalities and could provide comprehensive information for clinical diagnostics. This review discusses the advantages and challenges in developing dual-modality imaging probes. (authors)

  16. A Multiresolution Image Completion Algorithm for Compressing Digital Color Images

    Directory of Open Access Journals (Sweden)

    R. Gomathi

    2014-01-01

    Full Text Available This paper introduces a new framework for image coding that uses image inpainting method. In the proposed algorithm, the input image is subjected to image analysis to remove some of the portions purposefully. At the same time, edges are extracted from the input image and they are passed to the decoder in the compressed manner. The edges which are transmitted to decoder act as assistant information and they help inpainting process fill the missing regions at the decoder. Textural synthesis and a new shearlet inpainting scheme based on the theory of p-Laplacian operator are proposed for image restoration at the decoder. Shearlets have been mathematically proven to represent distributed discontinuities such as edges better than traditional wavelets and are a suitable tool for edge characterization. This novel shearlet p-Laplacian inpainting model can effectively reduce the staircase effect in Total Variation (TV inpainting model whereas it can still keep edges as well as TV model. In the proposed scheme, neural network is employed to enhance the value of compression ratio for image coding. Test results are compared with JPEG 2000 and H.264 Intracoding algorithms. The results show that the proposed algorithm works well.

  17. Dual-Modality PET/Ultrasound imaging of the Prostate

    Energy Technology Data Exchange (ETDEWEB)

    Huber, Jennifer S.; Moses, William W.; Pouliot, Jean; Hsu, I.C.

    2005-11-11

    Functional imaging with positron emission tomography (PET)will detect malignant tumors in the prostate and/or prostate bed, as well as possibly help determine tumor ''aggressiveness''. However, the relative uptake in a prostate tumor can be so great that few other anatomical landmarks are visible in a PET image. Ultrasound imaging with a transrectal probe provides anatomical detail in the prostate region that can be co-registered with the sensitive functional information from the PET imaging. Imaging the prostate with both PET and transrectal ultrasound (TRUS) will help determine the location of any cancer within the prostate region. This dual-modality imaging should help provide better detection and treatment of prostate cancer. LBNL has built a high performance positron emission tomograph optimized to image the prostate.Compared to a standard whole-body PET camera, our prostate-optimized PET camera has the same sensitivity and resolution, less backgrounds and lower cost. We plan to develop the hardware and software tools needed for a validated dual PET/TRUS prostate imaging system. We also plan to develop dual prostate imaging with PET and external transabdominal ultrasound, in case the TRUS system is too uncomfortable for some patients. We present the design and intended clinical uses for these dual imaging systems.

  18. Dual-Modality PET/Ultrasound imaging of the Prostate

    International Nuclear Information System (INIS)

    Huber, Jennifer S.; Moses, William W.; Pouliot, Jean; Hsu, I.C.

    2005-01-01

    Functional imaging with positron emission tomography (PET)will detect malignant tumors in the prostate and/or prostate bed, as well as possibly help determine tumor ''aggressiveness''. However, the relative uptake in a prostate tumor can be so great that few other anatomical landmarks are visible in a PET image. Ultrasound imaging with a transrectal probe provides anatomical detail in the prostate region that can be co-registered with the sensitive functional information from the PET imaging. Imaging the prostate with both PET and transrectal ultrasound (TRUS) will help determine the location of any cancer within the prostate region. This dual-modality imaging should help provide better detection and treatment of prostate cancer. LBNL has built a high performance positron emission tomograph optimized to image the prostate.Compared to a standard whole-body PET camera, our prostate-optimized PET camera has the same sensitivity and resolution, less backgrounds and lower cost. We plan to develop the hardware and software tools needed for a validated dual PET/TRUS prostate imaging system. We also plan to develop dual prostate imaging with PET and external transabdominal ultrasound, in case the TRUS system is too uncomfortable for some patients. We present the design and intended clinical uses for these dual imaging systems

  19. Optical imaging modalities: From design to diagnosis of skin cancer

    Science.gov (United States)

    Korde, Vrushali Raj

    This study investigates three high resolution optical imaging modalities to better detect and diagnose skin cancer. The ideal high resolution optical imaging system can visualize pre-malignant tissue growth non-invasively with resolution comparable to histology. I examined 3 modalities which approached this goal. The first method examined was high magnification microscopy of thin stained tissue sections, together with a statistical analysis of nuclear chromatin patterns termed Karyometry. This method has subcellular resolution, but it necessitates taking a biopsy at the desired tissue site and imaging the tissue ex-vivo. My part of this study was to develop an automated nuclear segmentation algorithm to segment cell nuclei in skin histology images for karyometric analysis. The results of this algorithm were compared to hand segmented cell nuclei in the same images, and it was concluded that the automated segmentations can be used for karyometric analysis. The second optical imaging modality I investigated was Optical Coherence Tomography (OCT). OCT is analogous to ultrasound, in which sound waves are delivered into the body and the echo time and reflected signal magnitude are measured. Due to the fast speed of light and detector temporal integration times, low coherence interferometry is needed to gate the backscattered light. OCT acquires cross sectional images, and has an axial resolution of 1-15 mum (depending on the source bandwidth) and a lateral resolution of 10-20 mum (depending on the sample arm optics). While it is not capable of achieving subcellular resolution, it is a non-invasive imaging modality. OCT was used in this study to evaluate skin along a continuum from normal to sun damaged to precancer. I developed algorithms to detect statistically significant differences between images of sun protected and sun damaged skin, as well as between undiseased and precancerous skin. An Optical Coherence Microscopy (OCM) endoscope was developed in the third

  20. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  1. Effects on MR images compression in tissue classification quality

    International Nuclear Information System (INIS)

    Santalla, H; Meschino, G; Ballarin, V

    2007-01-01

    It is known that image compression is required to optimize the storage in memory. Moreover, transmission speed can be significantly improved. Lossless compression is used without controversy in medicine, though benefits are limited. If we compress images lossy, where image can not be totally recovered; we can only recover an approximation. In this point definition of 'quality' is essential. What we understand for 'quality'? How can we evaluate a compressed image? Quality in images is an attribute whit several definitions and interpretations, which actually depend on the posterior use we want to give them. This work proposes a quantitative analysis of quality for lossy compressed Magnetic Resonance (MR) images, and their influence in automatic tissue classification, accomplished with these images

  2. Dual-modal photoacoustic and ultrasound imaging of dental implants

    Science.gov (United States)

    Lee, Donghyun; Park, Sungjo; Kim, Chulhong

    2018-02-01

    Dental implants are common method to replace decayed or broken tooth. As the implant treatment procedures varies according to the patients' jawbone, bone ridge, and sinus structure, appropriate examinations are necessary for successful treatment. Currently, radiographic examinations including periapical radiology, panoramic X-ray, and computed tomography are commonly used for diagnosing and monitoring. However, these radiographic examinations have limitations in that patients and operators are exposed to radioactivity and multiple examinations are performed during the treatment. In this study, we demonstrated photoacoustic (PA) and ultrasound (US) combined imaging of dental implant that can lower the total amount of absorbed radiation dose in dental implant treatment. An acoustic resolution PA macroscopy and a clinical PA/US system was used for dental implant imaging. The acquired dual modal PA/US imaging results support that the proposed photoacoustic imaging strategy can reduce the radiation dose rate during dental implant treatment.

  3. Compression of digital images in radiology. Results of a consensus conference; Kompression digitaler Bilddaten in der Radiologie. Ergebnisse einer Konsensuskonferenz

    Energy Technology Data Exchange (ETDEWEB)

    Loose, R. [Klinikum Nuernberg-Nord (Germany). Inst. fuer Diagnostische und Interventionelle Radiologie; Braunschweig, R. [BG Kliniken Bergmannstrost, Halle/Saale (Germany). Klinik fuer Bildgebende Diagnostik und Interventionsradiologie; Kotter, E. [Universitaetsklinikum Freiburg (Germany). Abt. Roentgendiagnostik; Mildenberger, P. [Mainz Univ. (Germany). Klinik und Poliklinik fuer Diagnostische und Interventionelle Radiologie; Simmler, R.; Wucherer, M. [Klinikum Nuernberg (Germany). Inst. fuer Medizinische Physik

    2009-01-15

    Purpose: Recommendations for lossy compression of digital radiological DICOM images in Germany by means of a consensus conference. The compression of digital radiological images was evaluated in many studies. Even though the results demonstrate full diagnostic image quality of modality-dependent compression between 1:5 and 1:200, there are only a few clinical applications. Materials and Methods: A consensus conference with approx. 80 interested participants (radiology, industry, physics, and agencies) without individual invitation was organized by the working groups AGIT and APT of the German Roentgen Society DRG to determine compression factors without loss of diagnostic image quality for different anatomical regions for CT, CR/DR, MR, RF/XA examinations. The consent level was specified as at least 66 %. Results: For individual modalities the following compression factors were recommended: CT (brain) 1:5, CT (all other applications) 1:8, CR/DR (all applications except mammography) 1:10, CR/DR (mammography) 1:15, MR (all applications) 1:7, RF/XA (fluoroscopy, DSA, cardiac angio) 1:6. The recommended compression ratios are valid for JPEG and JPEG 2000 /Wavelet compressions. Conclusion: The results may be understood as recommendations and indicate limits of compression factors with no expected reduction of diagnostic image quality. They are similar to the current national recommendations for Canada and England. (orig.)

  4. Image compression using the W-transform

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, W.D. Jr. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-12-31

    The authors present the W-transform for a multiresolution signal decomposition. One of the differences between the wavelet transform and W-transform is that the W-transform leads to a nonorthogonal signal decomposition. Another difference between the two is the manner in which the W-transform handles the endpoints (boundaries) of the signal. This approach does not restrict the length of the signal to be a power of two. Furthermore, it does not call for the extension of the signal thus, the W-transform is a convenient tool for image compression. They present the basic theory behind the W-transform and include experimental simulations to demonstrate its capabilities.

  5. High Bit-Depth Medical Image Compression With HEVC.

    Science.gov (United States)

    Parikh, Saurin S; Ruiz, Damian; Kalva, Hari; Fernandez-Escribano, Gerardo; Adzic, Velibor

    2018-03-01

    Efficient storing and retrieval of medical images has direct impact on reducing costs and improving access in cloud-based health care services. JPEG 2000 is currently the commonly used compression format for medical images shared using the DICOM standard. However, new formats such as high efficiency video coding (HEVC) can provide better compression efficiency compared to JPEG 2000. Furthermore, JPEG 2000 is not suitable for efficiently storing image series and 3-D imagery. Using HEVC, a single format can support all forms of medical images. This paper presents the use of HEVC for diagnostically acceptable medical image compression, focusing on compression efficiency compared to JPEG 2000. Diagnostically acceptable lossy compression and complexity of high bit-depth medical image compression are studied. Based on an established medically acceptable compression range for JPEG 2000, this paper establishes acceptable HEVC compression range for medical imaging applications. Experimental results show that using HEVC can increase the compression performance, compared to JPEG 2000, by over 54%. Along with this, a new method for reducing computational complexity of HEVC encoding for medical images is proposed. Results show that HEVC intra encoding complexity can be reduced by over 55% with negligible increase in file size.

  6. Acoustic Angiography: A New Imaging Modality for Assessing Microvasculature Architecture

    Directory of Open Access Journals (Sweden)

    Ryan C. Gessner

    2013-01-01

    Full Text Available The purpose of this paper is to provide the biomedical imaging community with details of a new high resolution contrast imaging approach referred to as “acoustic angiography.” Through the use of dual-frequency ultrasound transducer technology, images acquired with this approach possess both high resolution and a high contrast-to-tissue ratio, which enables the visualization of microvascular architecture without significant contribution from background tissues. Additionally, volumetric vessel-tissue integration can be visualized by using b-mode overlays acquired with the same probe. We present a brief technical overview of how the images are acquired, followed by several examples of images of both healthy and diseased tissue volumes. 3D images from alternate modalities often used in preclinical imaging, contrast-enhanced micro-CT and photoacoustics, are also included to provide a perspective on how acoustic angiography has qualitatively similar capabilities to these other techniques. These preliminary images provide visually compelling evidence to suggest that acoustic angiography may serve as a powerful new tool in preclinical and future clinical imaging.

  7. Lossless medical image compression with a hybrid coder

    Science.gov (United States)

    Way, Jing-Dar; Cheng, Po-Yuen

    1998-10-01

    The volume of medical image data is expected to increase dramatically in the next decade due to the large use of radiological image for medical diagnosis. The economics of distributing the medical image dictate that data compression is essential. While there is lossy image compression, the medical image must be recorded and transmitted lossless before it reaches the users to avoid wrong diagnosis due to the image data lost. Therefore, a low complexity, high performance lossless compression schematic that can approach the theoretic bound and operate in near real-time is needed. In this paper, we propose a hybrid image coder to compress the digitized medical image without any data loss. The hybrid coder is constituted of two key components: an embedded wavelet coder and a lossless run-length coder. In this system, the medical image is compressed with the lossy wavelet coder first, and the residual image between the original and the compressed ones is further compressed with the run-length coder. Several optimization schemes have been used in these coders to increase the coding performance. It is shown that the proposed algorithm is with higher compression ratio than run-length entropy coders such as arithmetic, Huffman and Lempel-Ziv coders.

  8. Medical image compression with fast Hartley transform

    International Nuclear Information System (INIS)

    Paik, C.H.; Fox, M.D.

    1988-01-01

    The purpose of data compression is storage and transmission of images with minimization of memory for storage and bandwidth for transmission, while maintaining robustness in the presence of transmission noise or storage medium errors. Here, the fast Hartley transform (FHT) is used for transformation and a new thresholding method is devised. The FHT is used instead of the fast Fourier transform (FFT), thus providing calculation at least as fast as that of the fastest algorithm of FFT. This real numbered transform requires only half the memory array space for saving of transform coefficients and allows for easy implementation on very large-scale integrated circuits because of the use of the same formula for both forward and inverse transformation and the conceptually straightforward algorithm. Threshold values were adaptively selected according to the correlation factor of each block of equally divided blocks of the image. Therefore, this approach provided a coding scheme that included maximum information with minimum image bandwidth. Overall, the results suggested that the Hartley transform adaptive thresholding approach results in improved fidelity, shorter decoding time, and greater robustness in the presence of noise than previous approaches

  9. Chronic granulomatous disease: Value of the newer imaging modalities

    International Nuclear Information System (INIS)

    Stricof, D.D.; Glazer, M.; Amendola, A.

    1984-01-01

    The contribution of computed tomography (CT), ultrasound (US), and nuclear medicine studies in the evaluation and management of seven patients with chronic granulatous disease was retrospectively reviewed. These modalities proved valuable in detecting sites of infection, particularly in the abdomen. Three patients had liver abscesses, two had suppurative retroperitoneal lymphadenopathy, one had empyema, and one hand a scrotal abscess. Furthermore, CT or US-guided percutaneous aspiration and/or drainage of infected material was successfully performed on three separate occasions in a single patient, obviating the need for surgery. The newer imaging modalities are useful in the prompt diagnosis and in some instances non-operative therapy of complications of chronic granulomatous disease. (orig.)

  10. Nanogels as imaging agents for modalities spanning the electromagnetic spectrum.

    Science.gov (United States)

    Chan, Minnie; Almutairi, Adah

    2016-01-21

    In the past few decades, advances in imaging equipment and protocols have expanded the role of imaging in in vivo diagnosis and disease management, especially in cancer. Traditional imaging agents have rapid clearance and low specificity for disease detection. To improve accuracy in disease identification, localization and assessment, novel nanomaterials are frequently explored as imaging agents to achieve high detection specificity and sensitivity. A promising material for this purpose are hydrogel nanoparticles, whose high hydrophilicity, biocompatibility, and tunable size in the nanometer range make them ideal for imaging. These nanogels (10 to 200 nm) can circumvent uptake by the reticuloendothelial system, allowing longer circulation times than small molecules. In addition, their size/surface properties can be further tailored to optimize their pharmacokinetics for imaging of a particular disease. Herein, we provide a comprehensive review of nanogels as imaging agents in various modalities with sources of signal spanning the electromagnetic spectrum, including MRI, NIR, UV-vis, and PET. Many materials and formulation methods will be reviewed to highlight the versatility of nanogels as imaging agents.

  11. An efficient algorithm for MR image reconstruction and compression

    International Nuclear Information System (INIS)

    Wang, Hang; Rosenfeld, D.; Braun, M.; Yan, Hong

    1992-01-01

    In magnetic resonance imaging (MRI), the original data are sampled in the spatial frequency domain. The sampled data thus constitute a set of discrete Fourier transform (DFT) coefficients. The image is usually reconstructed by taking inverse DFT. The image data may then be efficiently compressed using the discrete cosine transform (DCT). A method of using DCT to treat the sampled data is presented which combines two procedures, image reconstruction and data compression. This method may be particularly useful in medical picture archiving and communication systems where both image reconstruction and compression are important issues. 11 refs., 3 figs

  12. Accelerated Compressed Sensing Based CT Image Reconstruction.

    Science.gov (United States)

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  13. Accelerated Compressed Sensing Based CT Image Reconstruction

    Directory of Open Access Journals (Sweden)

    SayedMasoud Hashemi

    2015-01-01

    Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  14. Phase Imaging: A Compressive Sensing Approach

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Sebastian; Stevens, Andrew; Browning, Nigel D.; Pohl, Darius; Nielsch, Kornelius; Rellinghaus, Bernd

    2017-07-01

    Since Wolfgang Pauli posed the question in 1933, whether the probability densities |Ψ(r)|² (real-space image) and |Ψ(q)|² (reciprocal space image) uniquely determine the wave function Ψ(r) [1], the so called Pauli Problem sparked numerous methods in all fields of microscopy [2, 3]. Reconstructing the complete wave function Ψ(r) = a(r)e-iφ(r) with the amplitude a(r) and the phase φ(r) from the recorded intensity enables the possibility to directly study the electric and magnetic properties of the sample through the phase. In transmission electron microscopy (TEM), electron holography is by far the most established method for phase reconstruction [4]. Requiring a high stability of the microscope, next to the installation of a biprism in the TEM, holography cannot be applied to any microscope straightforwardly. Recently, a phase retrieval approach was proposed using conventional TEM electron diffractive imaging (EDI). Using the SAD aperture as reciprocal-space constraint, a localized sample structure can be reconstructed from its diffraction pattern and a real-space image using the hybrid input-output algorithm [5]. We present an alternative approach using compressive phase-retrieval [6]. Our approach does not require a real-space image. Instead, random complimentary pairs of checkerboard masks are cut into a 200 nm Pt foil covering a conventional TEM aperture (cf. Figure 1). Used as SAD aperture, subsequently diffraction patterns are recorded from the same sample area. Hereby every mask blocks different parts of gold particles on a carbon support (cf. Figure 2). The compressive sensing problem has the following formulation. First, we note that the complex-valued reciprocal-space wave-function is the Fourier transform of the (also complex-valued) real-space wave-function, Ψ(q) = F[Ψ(r)], and subsequently the diffraction pattern image is given by |Ψ(q)|2 = |F[Ψ(r)]|2. We want to find Ψ(r) given a few differently coded diffraction pattern measurements yn

  15. Modality prediction of biomedical literature images using multimodal feature representation

    Directory of Open Access Journals (Sweden)

    Pelka, Obioma

    2016-08-01

    Full Text Available This paper presents the modelling approaches performed to automatically predict the modality of images found in biomedical literature. Various state-of-the-art visual features such as Bag-of-Keypoints computed with dense SIFT descriptors, texture features and Joint Composite Descriptors were used for visual image representation. Text representation was obtained by vector quantisation on a Bag-of-Words dictionary generated using attribute importance derived from a χ-test. Computing the principal components separately on each feature, dimension reduction as well as computational load reduction was achieved. Various multiple feature fusions were adopted to supplement visual image information with corresponding text information. The improvement obtained when using multimodal features vs. visual or text features was detected, analysed and evaluated. Random Forest models with 100 to 500 deep trees grown by resampling, a multi class linear kernel SVM with C=0.05 and a late fusion of the two classifiers were used for modality prediction. A Random Forest classifier achieved a higher accuracy and computed Bag-of-Keypoints with dense SIFT descriptors proved to be a better approach than with Lowe SIFT.

  16. The relationship between compression force, image quality and ...

    African Journals Online (AJOL)

    Theoretically, an increase in breast compression gives a reduction in thickness without changing the density, resulting in improved image quality and reduced radiation dose. Aim. This study investigates the relationship between compression force, phantom thickness, image quality and radiation dose. The existence of a ...

  17. Photoacoustic and ultrasound dual-modality imaging for inflammatory arthritis

    Science.gov (United States)

    Xu, Guan; Chamberland, David; Girish, Gandikota; Wang, Xueding

    2014-03-01

    Arthritis is a leading cause of disability, affecting 46 million of the population in the U.S. Rendering new optical contrast in articular tissues at high spatial and temporal resolution, emerging photoacoustic imaging (PAI) combined with more established ultrasound (US) imaging technologies provides unique opportunities for diagnosis and treatment monitoring of inflammatory arthritis. In addition to capturing peripheral bone and soft tissue images, PAI has the capability to quantify hemodynamic properties including regional blood oxygenation and blood volume, both abnormal in synovial tissues affected by arthritis. Therefore, PAI, especially when performed together with US, should be of considerable help for further understanding the pathophysiology of arthritis as well as assisting in therapeutic decisions, including assessing the efficacy of new pharmacological therapies. In this paper, we will review our recent work on the development of PAI for application to the diagnostic imaging and therapeutic monitoring of inflammatory arthritis. We will present the imaging results from a home-built imaging system and another one based on a commercial US. The performance of PAI in evaluating pharmacological therapy on animal model of arthritis will be shown. Moreover, our resent work on PAI and US dual-modality imaging of human peripheral joints in vivo will also be presented.

  18. TU-C-BRD-01: Image Guided SBRT I: Multi-Modality 4D Imaging

    International Nuclear Information System (INIS)

    Cai, J; Mageras, G; Pan, T

    2014-01-01

    Motion management is one of the critical technical challenges for radiation therapy. 4D imaging has been rapidly adopted as essential tool to assess organ motion associated with respiratory breathing. A variety of 4D imaging techniques have been developed and are currently under development based on different imaging modalities such as CT, MRI, PET, and CBCT. Each modality provides specific and complementary information about organ and tumor respiratory motion. Effective use of each different technique or combined use of different techniques can introduce a comprehensive management of tumor motion. Specifically, these techniques have afforded tremendous opportunities to better define and delineate tumor volumes, more accurately perform patient positioning, and effectively apply highly conformal therapy techniques such as IMRT and SBRT. Successful implementation requires good understanding of not only each technique, including unique features, limitations, artifacts, imaging acquisition and process, but also how to systematically apply the information obtained from different imaging modalities using proper tools such as deformable image registration. Furthermore, it is important to understand the differences in the effects of breathing variation between different imaging modalities. A comprehensive motion management strategy using multi-modality 4D imaging has shown promise in improving patient care, but at the same time faces significant challenges. This session will focuses on the current status and advances in imaging respiration-induced organ motion with different imaging modalities: 4D-CT, 4D-MRI, 4D-PET, and 4D-CBCT/DTS. Learning Objectives: Understand the need and role of multimodality 4D imaging in radiation therapy. Understand the underlying physics behind each 4D imaging technique. Recognize the advantages and limitations of each 4D imaging technique

  19. Information theoretic bounds for compressed sensing in SAR imaging

    International Nuclear Information System (INIS)

    Jingxiong, Zhang; Ke, Yang; Jianzhong, Guo

    2014-01-01

    Compressed sensing (CS) is a new framework for sampling and reconstructing sparse signals from measurements significantly fewer than those prescribed by Nyquist rate in the Shannon sampling theorem. This new strategy, applied in various application areas including synthetic aperture radar (SAR), relies on two principles: sparsity, which is related to the signals of interest, and incoherence, which refers to the sensing modality. An important question in CS-based SAR system design concerns sampling rate necessary and sufficient for exact or approximate recovery of sparse signals. In the literature, bounds of measurements (or sampling rate) in CS have been proposed from the perspective of information theory. However, these information-theoretic bounds need to be reviewed and, if necessary, validated for CS-based SAR imaging, as there are various assumptions made in the derivations of lower and upper bounds on sub-Nyquist sampling rates, which may not hold true in CS-based SAR imaging. In this paper, information-theoretic bounds of sampling rate will be analyzed. For this, the SAR measurement system is modeled as an information channel, with channel capacity and rate-distortion characteristics evaluated to enable the determination of sampling rates required for recovery of sparse scenes. Experiments based on simulated data will be undertaken to test the theoretic bounds against empirical results about sampling rates required to achieve certain detection error probabilities

  20. Wavelet/scalar quantization compression standard for fingerprint images

    Energy Technology Data Exchange (ETDEWEB)

    Brislawn, C.M.

    1996-06-12

    US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class of potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.

  1. Imaging of radial wrist pain. I. Imaging modalities and anatomy

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ryan Ka Lok; Griffith, James F.; Ng, Alex Wing Hung [The Chinese University of Hong Kong, Department of Imaging and Interventional Radiology, Prince of Wales Hospital, Hong Kong, Shatin (China); Wong, Clara Wing Yee [The Chinese University of Hong Kong, Department of Orthopedics and Traumatology, Shatin (China)

    2014-06-15

    Radial wrist pain is a common clinical complaint. The relatively complex anatomy in this region, combined with the small size of the anatomical structures and occasionally subtle imaging findings, can pose problems when trying to localize the exact cause of pain. To fully comprehend the underlying pathology, one needs a good understanding of both radial-sided wrist anatomy and the relative merits of the different imaging techniques used to assess these structures. In part I of this review, these aspects will be discussed. (orig.)

  2. Fusion of different modalities of imaging the fist

    International Nuclear Information System (INIS)

    Verdenet, J.; Garbuio, P.; Runge, M.; Cardot, J.C.

    1997-01-01

    The standard radiographical pictures are not able always to bring out the fracture of one of the fist bones. In an early study it was shown that 40% of patients presenting a suspicion of fracture and in which the radio- image was normal, have had a fracture confirmed with quantification by MRI and scintigraphy. The last one does not allow to specify the localization and consequently we developed a code to fusion entirely automatically the radiologic image and the scintigraphic image using no external marker. The code has been installed on a PC and uses the Matlab environment. Starting from the histogram processing the contours are individualized on the interpolated radio- and scinti-images. For matching there are 3 freedom degrees: one of rotation and 2 of translation (in x and y axes). The internal axes of the forearm was chosen to effect the rotation and translation. The forehand thickness, identical for each modality, allows to match properly the images. We have obtained an anatomic image on which the contour and the hyper-fixating zones of the scintigraphy are added. On a set of 100 examinations we observed 38 fractures while the difference between a fracture of the scaphoid and of another fist bone is confirmed in 93% of cases

  3. Performance evaluation of emerging JPEGXR compression standard for medical images

    International Nuclear Information System (INIS)

    Basit, M.A.

    2012-01-01

    Medical images require loss less compression as a small error due to lossy compression may be considered as a diagnostic error. JPEG XR is the latest image compression standard designed for variety of applications and has a support for lossy and loss less modes. This paper provides in-depth performance evaluation of latest JPEGXR with existing image coding standards for medical images using loss less compression. Various medical images are used for evaluation and ten images of each organ are tested. Performance of JPEGXR is compared with JPEG2000 and JPEGLS using mean square error, peak signal to noise ratio, mean absolute error and structural similarity index. JPEGXR shows improvement of 20.73 dB and 5.98 dB over JPEGLS and JPEG2000 respectively for various test images used in experimentation. (author)

  4. Algorithm of imaging modalities in cases of mandibular fractures

    International Nuclear Information System (INIS)

    Mihailova, H.

    2009-01-01

    Mandibular fracture is the most common bone fracture of maxillo-facial trauma. Up to now the main method for examination of the mandible is radiography. The aim of the issue is to present an algorithm of imaging modalities for investigation of patients in cases of mandibular trauma. It consists of series of X ray techniques and views of the facial skull named mandibulo-facial. This standardizes mandibulo-facial series includes exactly determined four projections done by conventional X ray techniques: posterior-anterior view of skull (PA or AP), oblique view of the left mandible; oblique view of the right mandible; occipito-mental view. Using these four planned radiograms is obligatory for each mandibular trauma. Panoramic X-ray is obligatory in cases of apparatus availability; this abolish only oblique views (left and right). Occipito-mental view of the skull gives anatomically better the coronoid process of the mandible, the zygoma complex, the orbital edges and maxillar sinus than Waters projection. So mandibulo-facial series of four planned radiograms is not only for diagnostic of mandibular fractures, but as a screening of mandibulo-facial trauma too. Thus using algorithm of imaging modalities in cases of mandibular fracture leads to optimization of diagnostic process in patients with mandibular trauma. (author)

  5. Wavelet-based compression of pathological images for telemedicine applications

    Science.gov (United States)

    Chen, Chang W.; Jiang, Jianfei; Zheng, Zhiyong; Wu, Xue G.; Yu, Lun

    2000-05-01

    In this paper, we present the performance evaluation of wavelet-based coding techniques as applied to the compression of pathological images for application in an Internet-based telemedicine system. We first study how well suited the wavelet-based coding is as it applies to the compression of pathological images, since these images often contain fine textures that are often critical to the diagnosis of potential diseases. We compare the wavelet-based compression with the DCT-based JPEG compression in the DICOM standard for medical imaging applications. Both objective and subjective measures have been studied in the evaluation of compression performance. These studies are performed in close collaboration with expert pathologists who have conducted the evaluation of the compressed pathological images and communication engineers and information scientists who designed the proposed telemedicine system. These performance evaluations have shown that the wavelet-based coding is suitable for the compression of various pathological images and can be integrated well with the Internet-based telemedicine systems. A prototype of the proposed telemedicine system has been developed in which the wavelet-based coding is adopted for the compression to achieve bandwidth efficient transmission and therefore speed up the communications between the remote terminal and the central server of the telemedicine system.

  6. Correlation and image compression for limited-bandwidth CCD.

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, Douglas G.

    2005-07-01

    As radars move to Unmanned Aerial Vehicles with limited-bandwidth data downlinks, the amount of data stored and transmitted with each image becomes more significant. This document gives the results of a study to determine the effect of lossy compression in the image magnitude and phase on Coherent Change Detection (CCD). We examine 44 lossy compression types, plus lossless zlib compression, and test each compression method with over 600 CCD image pairs. We also derive theoretical predictions for the correlation for most of these compression schemes, which compare favorably with the experimental results. We recommend image transmission formats for limited-bandwidth programs having various requirements for CCD, including programs which cannot allow performance degradation and those which have stricter bandwidth requirements at the expense of CCD performance.

  7. Optimal Image Data Compression For Whole Slide Images

    Directory of Open Access Journals (Sweden)

    J. Isola

    2016-06-01

    Differences in WSI file sizes of scanned images deemed “visually lossless” were significant. If we set Hamamatsu Nanozoomer .NDPI file size (using its default “jpeg80 quality” as 100%, the size of a “visually lossless” JPEG2000 file was only 15-20% of that. Comparisons to Aperio and 3D-Histech files (.svs and .mrxs at their default settings yielded similar results. A further optimization of JPEG2000 was done by treating empty slide area as uniform white-grey surface, which could be maximally compressed. Using this algorithm, JPEG2000 file sizes were only half, or even smaller, of original JPEG2000. Variation was due to the proportion of empty slide area on the scan. We anticipate that wavelet-based image compression methods, such as JPEG2000, have a significant advantage in saving storage costs of scanned whole slide image. In routine pathology laboratories applying WSI technology widely to their histology material, absolute cost savings can be substantial.  

  8. A review of imaging modalities in pulmonary hypertension

    Directory of Open Access Journals (Sweden)

    Mona Ascha

    2017-01-01

    Full Text Available Pulmonary hypertension (PH is defined as resting mean pulmonary artery pressure ≥25 mmHg measured by right heart catheterization. PH is a progressive, life-threatening disease with a variety of etiologies. Swift and accurate diagnosis of PH and appropriate classification in etiologic group will allow for earlier treatment and improved outcomes. A number of imaging tools are utilized in the evaluation of PH, such as chest X-ray, computed tomography (CT, ventilation/perfusion (V/Q scan, and cardiac magnetic resonance imaging. Newer imaging tools such as dual-energy CT and single-photon emission computed tomography/computed tomography V/Q scanning have also emerged; however, their place in the diagnostic evaluation of PH remains to be determined. In general, each imaging technique provides incremental information, with varying degrees of sensitivity and specificity, which helps suspect the presence and identify the etiology of PH. The present study aims to provide a comprehensive review of the utility, advantages, and shortcomings of the imaging modalities that may be used to evaluate patients with PH.

  9. Improved proton computed tomography by dual modality image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, David C., E-mail: dch@ki.au.dk; Bassler, Niels [Experimental Clinical Oncology, Aarhus University, 8000 Aarhus C (Denmark); Petersen, Jørgen Breede Baltzer [Medical Physics, Aarhus University Hospital, 8000 Aarhus C (Denmark); Sørensen, Thomas Sangild [Computer Science, Aarhus University, 8000 Aarhus C, Denmark and Clinical Medicine, Aarhus University, 8200 Aarhus N (Denmark)

    2014-03-15

    Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360

  10. Improved proton computed tomography by dual modality image reconstruction

    International Nuclear Information System (INIS)

    Hansen, David C.; Bassler, Niels; Petersen, Jørgen Breede Baltzer; Sørensen, Thomas Sangild

    2014-01-01

    Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360

  11. Biomedical imaging modality classification using combined visual features and textual terms.

    Science.gov (United States)

    Han, Xian-Hua; Chen, Yen-Wei

    2011-01-01

    We describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign (ImageCLEF). This paper is focused on the process of feature extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

  12. Image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing

    Science.gov (United States)

    Zhou, Nanrun; Pan, Shumin; Cheng, Shan; Zhou, Zhihong

    2016-08-01

    Most image encryption algorithms based on low-dimensional chaos systems bear security risks and suffer encryption data expansion when adopting nonlinear transformation directly. To overcome these weaknesses and reduce the possible transmission burden, an efficient image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing is proposed. The original image is measured by the measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the cycle shift operation controlled by a hyper-chaotic system. Cycle shift operation can change the values of the pixels efficiently. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys distribution simultaneously as a nonlinear encryption system. Simulation results verify the validity and the reliability of the proposed algorithm with acceptable compression and security performance.

  13. Acceptable levels of digital image compression in chest radiology

    International Nuclear Information System (INIS)

    Smith, I.

    2000-01-01

    The introduction of picture archival and communications systems (PACS) and teleradiology has prompted an examination of techniques that optimize the storage capacity and speed of digital storage and distribution networks. The general acceptance of the move to replace conventional screen-film capture with computed radiography (CR) is an indication that clinicians within the radiology community are willing to accept images that have been 'compressed'. The question to be answered, therefore, is what level of compression is acceptable. The purpose of the present study is to provide an assessment of the ability of a group of imaging professionals to determine whether an image has been compressed. To undertake this study a single mobile chest image, selected for the presence of some subtle pathology in the form of a number of septal lines in both costphrenic angles, was compressed to levels of 10:1, 20:1 and 30:1. These images were randomly ordered and shown to the observers for interpretation. Analysis of the responses indicates that in general it was not possible to distinguish the original image from its compressed counterparts. Furthermore, a preference appeared to be shown for images that have undergone low levels of compression. This preference can most likely be attributed to the 'de-noising' effect of the compression algorithm at low levels. Copyright (1999) Blackwell Science Pty. Ltd

  14. Halftoning processing on a JPEG-compressed image

    Science.gov (United States)

    Sibade, Cedric; Barizien, Stephane; Akil, Mohamed; Perroton, Laurent

    2003-12-01

    Digital image processing algorithms are usually designed for the raw format, that is on an uncompressed representation of the image. Therefore prior to transforming or processing a compressed format, decompression is applied; then, the result of the processing application is finally re-compressed for further transfer or storage. The change of data representation is resource-consuming in terms of computation, time and memory usage. In the wide format printing industry, this problem becomes an important issue: e.g. a 1 m2 input color image, scanned at 600 dpi exceeds 1.6 GB in its raw representation. However, some image processing algorithms can be performed in the compressed-domain, by applying an equivalent operation on the compressed format. This paper is presenting an innovative application of the halftoning processing operation by screening, to be applied on JPEG-compressed image. This compressed-domain transform is performed by computing the threshold operation of the screening algorithm in the DCT domain. This algorithm is illustrated by examples for different halftone masks. A pre-sharpening operation, applied on a JPEG-compressed low quality image is also described; it allows to de-noise and to enhance the contours of this image.

  15. Combining Different Modalities for 3D Imaging of Biological Objects

    CERN Document Server

    Tsyganov, E; Kulkarni, P; Mason, R; Parkey, R; Seliuonine, S; Shay, J; Soesbe, T; Zhezher, V; Zinchenko, A I

    2005-01-01

    A resolution enhanced NaI(Tl)-scintillator micro-SPECT device using pinhole collimator geometry has been built and tested with small animals. This device was constructed based on a depth-of-interaction measurement using a thick scintillator crystal and a position sensitive PMT to measure depth-dependent scintillator light profiles. Such a measurement eliminates the parallax error that degrades the high spatial resolution required for small animal imaging. This novel technique for 3D gamma-ray detection was incorporated into the micro-SPECT device and tested with a $^{57}$Co source and $^{98m}$Tc-MDP injected in mice body. To further enhance the investigating power of the tomographic imaging different imaging modalities can be combined. In particular, as proposed and shown in this paper, the optical imaging permits a 3D reconstruction of the animal's skin surface thus improving visualization and making possible depth-dependent corrections, necessary for bioluminescence 3D reconstruction in biological objects. ...

  16. Combining different modalities for 3D imaging of biological objects

    International Nuclear Information System (INIS)

    Tsyganov, Eh.; Antich, P.; Kulkarni, P.; Mason, R.; Parkey, R.; Seliuonine, S.; Shay, J.; Soesbe, T.; Zhezher, V.; Zinchenko, A.

    2005-01-01

    A resolution enhanced NaI(Tl)-scintillator micro-SPECT device using pinhole collimator geometry has been built and tested with small animals. This device was constructed based on a depth-of-interaction measurement using a thick scintillator crystal and a position sensitive PMT to measure depth-dependent scintillator light profiles. Such a measurement eliminates the parallax error that degrades the high spatial resolution required for small animal imaging. This novel technique for 3D gamma-ray detection was incorporated into the micro-SPECT device and tested with a 57 Co source and 98m Tc-MDP injected in mice body. To further enhance the investigating power of the tomographic imaging different imaging modalities can be combined. In particular, as proposed and shown, the optical imaging permits a 3D reconstruction of the animal's skin surface thus improving visualization and making possible depth-dependent corrections, necessary for bioluminescence 3D reconstruction in biological objects. This structural information can provide even more detail if the x-ray tomography is used as presented in the paper

  17. Moving image compression and generalization capability of constructive neural networks

    Science.gov (United States)

    Ma, Liying; Khorasani, Khashayar

    2001-03-01

    To date numerous techniques have been proposed to compress digital images to ease their storage and transmission over communication channels. Recently, a number of image compression algorithms using Neural Networks NNs have been developed. Particularly, several constructive feed-forward neural networks FNNs have been proposed by researchers for image compression, and promising results have been reported. At the previous SPIE AeroSense conference 2000, we proposed to use a constructive One-Hidden-Layer Feedforward Neural Network OHL-FNN for compressing digital images. In this paper, we first investigate the generalization capability of the proposed OHL-FNN in the presence of additive noise for network training and/ or generalization. Extensive experimental results for different scenarios are presented. It is revealed that the constructive OHL-FNN is not as robust to additive noise in input image as expected. Next, the constructive OHL-FNN is applied to moving images, video sequences. The first, or other specified frame in a moving image sequence is used to train the network. The remaining moving images that follow are then generalized/compressed by this trained network. Three types of correlation-like criteria measuring the similarity of any two images are introduced. The relationship between the generalization capability of the constructed net and the similarity of images is investigated in some detail. It is shown that the constructive OHL-FNN is promising even for changing images such as those extracted from a football game.

  18. Extreme compression for extreme conditions: pilot study to identify optimal compression of CT images using MPEG-4 video compression.

    Science.gov (United States)

    Peterson, P Gabriel; Pak, Sung K; Nguyen, Binh; Jacobs, Genevieve; Folio, Les

    2012-12-01

    This study aims to evaluate the utility of compressed computed tomography (CT) studies (to expedite transmission) using Motion Pictures Experts Group, Layer 4 (MPEG-4) movie formatting in combat hospitals when guiding major treatment regimens. This retrospective analysis was approved by Walter Reed Army Medical Center institutional review board with a waiver for the informed consent requirement. Twenty-five CT chest, abdomen, and pelvis exams were converted from Digital Imaging and Communications in Medicine to MPEG-4 movie format at various compression ratios. Three board-certified radiologists reviewed various levels of compression on emergent CT findings on 25 combat casualties and compared with the interpretation of the original series. A Universal Trauma Window was selected at -200 HU level and 1,500 HU width, then compressed at three lossy levels. Sensitivities and specificities for each reviewer were calculated along with 95 % confidence intervals using the method of general estimating equations. The compression ratios compared were 171:1, 86:1, and 41:1 with combined sensitivities of 90 % (95 % confidence interval, 79-95), 94 % (87-97), and 100 % (93-100), respectively. Combined specificities were 100 % (85-100), 100 % (85-100), and 96 % (78-99), respectively. The introduction of CT in combat hospitals with increasing detectors and image data in recent military operations has increased the need for effective teleradiology; mandating compression technology. Image compression is currently used to transmit images from combat hospital to tertiary care centers with subspecialists and our study demonstrates MPEG-4 technology as a reasonable means of achieving such compression.

  19. Imaging by multiple modalities of patients with a carotidynia syndrome

    Energy Technology Data Exchange (ETDEWEB)

    Kosaka, Nobuyuki; Uematsu, Hidemasa; Kimura, Hirohiko; Itoh, Harumi [University of Fukui, Department of Radiology, Faculty of Medical Sciences, Fukui (Japan); Sagoh, Tadashi; Noguchi, Masato [Fukui Red Cross Hospital, Department of Radiology, Fukui (Japan); Miyayama, Shiro [Fukuiken Saiseikai Hospital, Department of Diagnostic Radiology, Fukui (Japan)

    2007-09-15

    The purpose of this article is to familiarize readers with the clinical syndrome of carotidynia. In the past, the International Headache Society (IHS) described idiopathic carotidynia as a diagnostic entity consisting of a self-limiting neck pain syndrome and tenderness over the carotid bifurcation without structural abnormality and then recently removed it from its classification. Although the clinical criteria of carotidynia in the former classification of the IHS included the absence of structural abnormality, several publications have demonstrated associated radiological findings and have described the usefulness of radiological investigations in diagnosing this syndrome. In this paper, we report four additional cases with a carotidynia clinical syndrome (according to the former classification) and the presence of abnormal soft tissue infiltration surrounding the symptomatic carotid artery as demonstrated by multiple imaging modalities, without any other underlying cause for the carotid pain syndrome. Our findings support the hypothesis that carotidynia could be a distinct disease entity, possibly caused by inflammation. (orig.)

  20. Imaging by multiple modalities of patients with a carotidynia syndrome

    International Nuclear Information System (INIS)

    Kosaka, Nobuyuki; Uematsu, Hidemasa; Kimura, Hirohiko; Itoh, Harumi; Sagoh, Tadashi; Noguchi, Masato; Miyayama, Shiro

    2007-01-01

    The purpose of this article is to familiarize readers with the clinical syndrome of carotidynia. In the past, the International Headache Society (IHS) described idiopathic carotidynia as a diagnostic entity consisting of a self-limiting neck pain syndrome and tenderness over the carotid bifurcation without structural abnormality and then recently removed it from its classification. Although the clinical criteria of carotidynia in the former classification of the IHS included the absence of structural abnormality, several publications have demonstrated associated radiological findings and have described the usefulness of radiological investigations in diagnosing this syndrome. In this paper, we report four additional cases with a carotidynia clinical syndrome (according to the former classification) and the presence of abnormal soft tissue infiltration surrounding the symptomatic carotid artery as demonstrated by multiple imaging modalities, without any other underlying cause for the carotid pain syndrome. Our findings support the hypothesis that carotidynia could be a distinct disease entity, possibly caused by inflammation. (orig.)

  1. CoGI: Towards Compressing Genomes as an Image.

    Science.gov (United States)

    Xie, Xiaojing; Zhou, Shuigeng; Guan, Jihong

    2015-01-01

    Genomic science is now facing an explosive increase of data thanks to the fast development of sequencing technology. This situation poses serious challenges to genomic data storage and transferring. It is desirable to compress data to reduce storage and transferring cost, and thus to boost data distribution and utilization efficiency. Up to now, a number of algorithms / tools have been developed for compressing genomic sequences. Unlike the existing algorithms, most of which treat genomes as one-dimensional text strings and compress them based on dictionaries or probability models, this paper proposes a novel approach called CoGI (the abbreviation of Compressing Genomes as an Image) for genome compression, which transforms the genomic sequences to a two-dimensional binary image (or bitmap), then applies a rectangular partition coding algorithm to compress the binary image. CoGI can be used as either a reference-based compressor or a reference-free compressor. For the former, we develop two entropy-based algorithms to select a proper reference genome. Performance evaluation is conducted on various genomes. Experimental results show that the reference-based CoGI significantly outperforms two state-of-the-art reference-based genome compressors GReEn and RLZ-opt in both compression ratio and compression efficiency. It also achieves comparable compression ratio but two orders of magnitude higher compression efficiency in comparison with XM--one state-of-the-art reference-free genome compressor. Furthermore, our approach performs much better than Gzip--a general-purpose and widely-used compressor, in both compression speed and compression ratio. So, CoGI can serve as an effective and practical genome compressor. The source code and other related documents of CoGI are available at: http://admis.fudan.edu.cn/projects/cogi.htm.

  2. Breast US as primary imaging modality for diagnosing gynecomastia.

    Science.gov (United States)

    Telegrafo, M; Introna, T; Coi, L; Cornacchia, I; Rella, L; Stabile Ianora, A A; Angelelli, G; Moschetta, M

    2016-01-01

    To assess the role of breast US in diagnosing and classifying gynecomastia as the primary imaging modality and to compare US findings and classification system with the mammographic ones. 48 patients suspected of having gynecomastia underwent mammography and US. Two radiologists in consensus retrospectively evaluated mammograms and sonograms. Both US and mammographic images were evaluated categorizing gynecomastia into non-mass, nodular and flame shaped patterns. The two category assignations were compared in order to find any difference. The reference standard for both the classification systems was represented by the cytological examination in 18 out of 44 cases (41%) and the six-month US follow-up in the remaining cases. The US examination revealed pseudo-gynecomastia in 4/48 (8%) and true gynecomastia in the remaining 44 (92%). Gynecomastia was bilateral in 25/44 cases (57%) and unilateral in the remaining 19 (43%). The cases of true gynecomastia included non mass shape in 26/44 cases (59%), nodular shape in 12 (27%) and flame shape in 6 (14%). The mammographic examination revealed the same results as compared with US findings. 18/44 (41%) patients affected by nodular or dendritic gynecomastia underwent cytological examination confirming the presence of glandular tissue and the benign nature of the clinical condition. US could be proposed as the primary imaging tool for diagnosing and classifying gynecomastia, avoiding unnecessary Xray examinations or invasive procedures in case of diffuse gynecomastia. In case of nodular or dendritic patterns, biopsy remains mandatory for a definitive diagnosis.

  3. Imaging modalities in radiation treatment planning of brain tumors

    International Nuclear Information System (INIS)

    Georgiev, D.

    2009-01-01

    The radiation therapy is a standard treatment after surgery for most of malignant and some of benignant brain tumors. The restriction in acquiring local tumor control is an inability in realization of high dose without causing radiation necrosis in irradiated area and sparing normal tissues. The development of imaging modalities during the last years is responsible for better treatment results and lower early and late toxicity. Essential is the role of image methods not only in the diagnosis and also in the precise anatomical (during last years also functional) localisation, spreading of the tumor, treatment planning process and the effects of the treatment. Target delineation is one of the great geometrical uncertainties in the treatment planning process. Early studies on the use of CT in treatment planning documented that tumor coverage without CT was clearly inadequate in 20% of the patients and marginal in another 27 %. The image fusion of CT, MBI and PET and also the use of contrast materia helps to get over those restrictions. The use of contrast material enhances the signal in 10 % of the patients with glioblastoma multiform and in a higher percentage of the patients with low-grade gliomas

  4. Dynamic CT perfusion image data compression for efficient parallel processing.

    Science.gov (United States)

    Barros, Renan Sales; Olabarriaga, Silvia Delgado; Borst, Jordi; van Walderveen, Marianne A A; Posthuma, Jorrit S; Streekstra, Geert J; van Herk, Marcel; Majoie, Charles B L M; Marquering, Henk A

    2016-03-01

    The increasing size of medical imaging data, in particular time series such as CT perfusion (CTP), requires new and fast approaches to deliver timely results for acute care. Cloud architectures based on graphics processing units (GPUs) can provide the processing capacity required for delivering fast results. However, the size of CTP datasets makes transfers to cloud infrastructures time-consuming and therefore not suitable in acute situations. To reduce this transfer time, this work proposes a fast and lossless compression algorithm for CTP data. The algorithm exploits redundancies in the temporal dimension and keeps random read-only access to the image elements directly from the compressed data on the GPU. To the best of our knowledge, this is the first work to present a GPU-ready method for medical image compression with random access to the image elements from the compressed data.

  5. MEDICAL IMAGE COMPRESSION USING HYBRID CODER WITH FUZZY EDGE DETECTION

    Directory of Open Access Journals (Sweden)

    K. Vidhya

    2011-02-01

    Full Text Available Medical imaging techniques produce prohibitive amounts of digitized clinical data. Compression of medical images is a must due to large memory space required for transmission and storage. This paper presents an effective algorithm to compress and to reconstruct medical images. The proposed algorithm first extracts edge information of medical images by using fuzzy edge detector. The images are decomposed using Cohen-Daubechies-Feauveau (CDF wavelet. The hybrid technique utilizes the efficient wavelet based compression algorithms such as JPEG2000 and Set Partitioning In Hierarchical Trees (SPIHT. The wavelet coefficients in the approximation sub band are encoded using tier 1 part of JPEG2000. The wavelet coefficients in the detailed sub bands are encoded using SPIHT. Consistent quality images are produced by this method at a lower bit rate compared to other standard compression algorithms. Two main approaches to assess image quality are objective testing and subjective testing. The image quality is evaluated by objective quality measures. Objective measures correlate well with the perceived image quality for the proposed compression algorithm.

  6. Imaging modalities for the non-invasive diagnosis of endometriosis.

    Science.gov (United States)

    Nisenblat, Vicki; Bossuyt, Patrick M M; Farquhar, Cindy; Johnson, Neil; Hull, M Louise

    2016-02-26

    About 10% of women of reproductive age suffer from endometriosis. Endometriosis is a costly chronic disease that causes pelvic pain and subfertility. Laparoscopy, the gold standard diagnostic test for endometriosis, is expensive and carries surgical risks. Currently, no non-invasive tests that can be used to accurately diagnose endometriosis are available in clinical practice. This is the first review of diagnostic test accuracy of imaging tests for endometriosis that uses Cochrane methods to provide an update on the rapidly expanding literature in this field. • To provide estimates of the diagnostic accuracy of imaging modalities for the diagnosis of pelvic endometriosis, ovarian endometriosis and deeply infiltrating endometriosis (DIE) versus surgical diagnosis as a reference standard.• To describe performance of imaging tests for mapping of deep endometriotic lesions in the pelvis at specific anatomical sites.Imaging tests were evaluated as replacement tests for diagnostic surgery and as triage tests that would assist decision making regarding diagnostic surgery for endometriosis. We searched the following databases to 20 April 2015: MEDLINE, CENTRAL, EMBASE, CINAHL, PsycINFO, Web of Science, LILACS, OAIster, TRIP, ClinicalTrials.gov, MEDION, DARE, and PubMed. Searches were not restricted to a particular study design or language nor to specific publication dates. The search strategy incorporated words in the title, abstracts, text words across the record and medical subject headings (MeSH). We considered published peer-reviewed cross-sectional studies and randomised controlled trials of any size that included prospectively recruited women of reproductive age suspected of having one or more of the following target conditions: endometrioma, pelvic endometriosis, DIE or endometriotic lesions at specific intrapelvic anatomical locations. We included studies that compared the diagnostic test accuracy of one or more imaging modalities versus findings of surgical

  7. Wavelet compression algorithm applied to abdominal ultrasound images

    International Nuclear Information System (INIS)

    Lin, Cheng-Hsun; Pan, Su-Feng; LU, Chin-Yuan; Lee, Ming-Che

    2006-01-01

    We sought to investigate acceptable compression ratios of lossy wavelet compression on 640 x 480 x 8 abdominal ultrasound (US) images. We acquired 100 abdominal US images with normal and abnormal findings from the view station of a 932-bed teaching hospital. The US images were then compressed at quality factors (QFs) of 3, 10, 30, and 50 followed outcomes of a pilot study. This was equal to the average compression ratios of 4.3:1, 8.5:1, 20:1 and 36.6:1, respectively. Four objective measurements were carried out to examine and compare the image degradation between original and compressed images. Receiver operating characteristic (ROC) analysis was also introduced for subjective assessment. Five experienced and qualified radiologists as reviewers blinded to corresponding pathological findings, analysed paired 400 randomly ordered images with two 17-inch thin film transistor/liquid crystal display (TFT/LCD) monitors. At ROC analysis, the average area under curve (Az) for US abdominal image was 0.874 at the ratio of 36.6:1. The compressed image size was only 2.7% for US original at this ratio. The objective parameters showed the higher the mean squared error (MSE) or root mean squared error (RMSE) values, the poorer the image quality. The higher signal-to-noise ratio (SNR) or peak signal-to-noise ratio (PSNR) values indicated better image quality. The average RMSE, PSNR at 36.6:1 for US were 4.84 ± 0.14, 35.45 dB, respectively. This finding suggests that, on the basis of the patient sample, wavelet compression of abdominal US to a ratio of 36.6:1 did not adversely affect diagnostic performance or evaluation error for radiologists' interpretation so as to risk affecting diagnosis

  8. Image compression software for the SOHO LASCO and EIT experiments

    Science.gov (United States)

    Grunes, Mitchell R.; Howard, Russell A.; Hoppel, Karl; Mango, Stephen A.; Wang, Dennis

    1994-01-01

    This paper describes the lossless and lossy image compression algorithms to be used on board the Solar Heliospheric Observatory (SOHO) in conjunction with the Large Angle Spectrometric Coronograph and Extreme Ultraviolet Imaging Telescope experiments. It also shows preliminary results obtained using similar prior imagery and discusses the lossy compression artifacts which will result. This paper is in part intended for the use of SOHO investigators who need to understand the results of SOHO compression in order to better allocate the transmission bits which they have been allocated.

  9. Localisation of epileptic foci using novel imaging modalities

    Science.gov (United States)

    De Ciantis, Alessio; Lemieux, Louis

    2013-01-01

    Purpose of review This review examines recent reports on the use of advanced techniques to map the regions and networks involved during focal epileptic seizure generation in humans. Recent findings A number of imaging techniques are capable of providing new localizing information on the ictal processes and epileptogenic zone. Evaluating the clinical utility of these findings has been mainly performed through post-hoc comparison with the findings of invasive EEG and ictal single-photon emission computed tomography, using postsurgical seizure reduction as the main outcome measure. Added value has been demonstrated in MRI-negative cases. Improved understanding of the human ictiogenic processes and the focus vs. network hypothesis is likely to result from the application of multimodal techniques that combine electrophysiological, semiological, and whole-brain coverage of brain activity changes. Summary On the basis of recent research in the field of neuroimaging, several novel imaging modalities have been improved and developed to provide information about the localization of epileptic foci. PMID:23823464

  10. Hyperpolarized 129Xe MRI: A viable functional lung imaging modality?

    International Nuclear Information System (INIS)

    Patz, Samuel; Hersman, F. William; Muradian, Iga; Hrovat, Mirko I.; Ruset, Iulian C.; Ketel, Stephen; Jacobson, Francine; Topulos, George P.; Hatabu, Hiroto; Butler, James P.

    2007-01-01

    The majority of researchers investigating hyperpolarized gas MRI as a candidate functional lung imaging modality have used 3 He as their imaging agent of choice rather than 129 Xe. This preference has been predominantly due to, 3 He providing stronger signals due to higher levels of polarization and higher gyromagnetic ratio, as well as its being easily available to more researchers due to availability of polarizers (USA) or ease of gas transport (Europe). Most researchers agree, however, that hyperpolarized 129 Xe will ultimately emerge as the imaging agent of choice due to its unlimited supply in nature and its falling cost. Our recent polarizer technology delivers vast improvements in hyperpolarized 129 Xe output. Using this polarizer, we have demonstrated the unique property of xenon to measure alveolar surface area noninvasively. In this article, we describe our human protocols and their safety, and our results for the measurement of the partial pressure of pulmonary oxygen (pO 2 ) by observation of 129 Xe signal decay. We note that the measurement of pO 2 by observation of 129 Xe signal decay is more complex than that for 3 He because of an additional signal loss mechanism due to interphase diffusion of 129 Xe from alveolar gas spaces to septal tissue. This results in measurements of an equivalent pO 2 that accounts for both traditional T 1 decay from pO 2 and that from interphase diffusion. We also provide an update on new technological advancements that form the foundation for an improved compact design polarizer as well as improvements that provide another order-of-magnitude scale-up in xenon polarizer output

  11. Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

    International Nuclear Information System (INIS)

    Joshi, Bishnu P.; Wang, Thomas D.

    2010-01-01

    Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research

  12. Compositional-prior-guided image reconstruction algorithm for multi-modality imaging

    Science.gov (United States)

    Fang, Qianqian; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

    2010-01-01

    The development of effective multi-modality imaging methods typically requires an efficient information fusion model, particularly when combining structural images with a complementary imaging modality that provides functional information. We propose a composition-based image segmentation method for X-ray digital breast tomosynthesis (DBT) and a structural-prior-guided image reconstruction for a combined DBT and diffuse optical tomography (DOT) breast imaging system. Using the 3D DBT images from 31 clinically measured healthy breasts, we create an empirical relationship between the X-ray intensities for adipose and fibroglandular tissue. We use this relationship to then segment another 58 healthy breast DBT images from 29 subjects into compositional maps of different tissue types. For each breast, we build a weighted-graph in the compositional space and construct a regularization matrix to incorporate the structural priors into a finite-element-based DOT image reconstruction. Use of the compositional priors enables us to fuse tissue anatomy into optical images with less restriction than when using a binary segmentation. This allows us to recover the image contrast captured by DOT but not by DBT. We show that it is possible to fine-tune the strength of the structural priors by changing a single regularization parameter. By estimating the optical properties for adipose and fibroglandular tissue using the proposed algorithm, we found the results are comparable or superior to those estimated with expert-segmentations, but does not involve the time-consuming manual selection of regions-of-interest. PMID:21258460

  13. Magnetic resonance imaging validation of pituitary gland compression and distortion by typical sellar pathology.

    Science.gov (United States)

    Cho, Charles H; Barkhoudarian, Garni; Hsu, Liangge; Bi, Wenya Linda; Zamani, Amir A; Laws, Edward R

    2013-12-01

    Identification of the normal pituitary gland is an important component of presurgical planning, defining many aspects of the surgical approach and facilitating normal gland preservation. Magnetic resonance imaging is a proven imaging modality for optimal soft-tissue contrast discrimination in the brain. This study is designed to validate the accuracy of localization of the normal pituitary gland with MRI in a cohort of surgical patients with pituitary mass lesions, and to evaluate for correlation between presurgical pituitary hormone values and pituitary gland characteristics on neuroimaging. Fifty-eight consecutive patients with pituitary mass lesions were included in the study. Anterior pituitary hormone levels were measured preoperatively in all patients. Video recordings from the endoscopic or microscopic surgical procedures were available for evaluation in 47 cases. Intraoperative identification of the normal gland was possible in 43 of 58 cases. Retrospective MR images were reviewed in a blinded fashion for the 43 cases, emphasizing the position of the normal gland and the extent of compression and displacement by the lesion. There was excellent agreement between imaging and surgery in 84% of the cases for normal gland localization, and in 70% for compression or noncompression of the normal gland. There was no consistent correlation between preoperative pituitary dysfunction and pituitary gland localization on imaging, gland identification during surgery, or pituitary gland compression. Magnetic resonance imaging proved to be accurate in identifying the normal gland in patients with pituitary mass lesions, and was useful for preoperative surgical planning.

  14. Optimization of wavelet decomposition for image compression and feature preservation.

    Science.gov (United States)

    Lo, Shih-Chung B; Li, Huai; Freedman, Matthew T

    2003-09-01

    A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

  15. Contributions to HEVC Prediction for Medical Image Compression

    OpenAIRE

    Guarda, André Filipe Rodrigues

    2016-01-01

    Medical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which allow easier and more accurate medical diagnosis. However, this increase in resolution demands a growing amount of data to be stored and transmitted. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compressi...

  16. Medical image compression by using three-dimensional wavelet transformation

    International Nuclear Information System (INIS)

    Wang, J.; Huang, H.K.

    1996-01-01

    This paper proposes a three-dimensional (3-D) medical image compression method for computed tomography (CT) and magnetic resonance (MR) that uses a separable nonuniform 3-D wavelet transform. The separable wavelet transform employs one filter bank within two-dimensional (2-D) slices and then a second filter bank on the slice direction. CT and MR image sets normally have different resolutions within a slice and between slices. The pixel distances within a slice are normally less than 1 mm and the distance between slices can vary from 1 mm to 10 mm. To find the best filter bank in the slice direction, the authors use the various filter banks in the slice direction and compare the compression results. The results from the 12 selected MR and CT image sets at various slice thickness show that the Haar transform in the slice direction gives the optimum performance for most image sets, except for a CT image set which has 1 mm slice distance. Compared with 2-D wavelet compression, compression ratios of the 3-D method are about 70% higher for CT and 35% higher for MR image sets at a peak signal to noise ratio (PSNR) of 50 dB. In general, the smaller the slice distance, the better the 3-D compression performance

  17. Imaging modalities used to confirm diaphragmatic hernia in small animals

    International Nuclear Information System (INIS)

    Williams, J.; Leveille, R.; Myer, C.W.

    1998-01-01

    When a patient is presented for treatment following a traumatic accident such as being hit by a car, thoracic radiographs are usually an integral part of the overall diagnostic evaluation. Diagnosis at diaphragmatic hernia (DH) is often challenging in small animals. The thorax may contain substantial fluid, thereby masking the presence of cranially displaced abdominal soft tissues (e.g., liver or spleen). The most common cause of decreased radiographic visualization of the diaphragm on survey radiographs is pleural fluid; however, the second most common cause is DH. Obviously, if a gas-filledviscus is identified within the thoracic cavity on survey radiographs, the diagnosis of DH is straightforward and relatively routine. If, however, there is substantial pleural effusion and the herniated structure is a soft tissue parenchymal organ (e.g., liver or spleen), the diagnosis is less clearly defined on survey radiographs. This review discusses the various imaging modalities (survey, positional, and contrast-enhanced radiographs and ultrasonography) that can be used in the diagnosis or confirmation of DH

  18. Cellular automata codebooks applied to compact image compression

    Directory of Open Access Journals (Sweden)

    Radu DOGARU

    2006-12-01

    Full Text Available Emergent computation in semi-totalistic cellular automata (CA is used to generate a set of basis (or codebook. Such codebooks are convenient for simple and circuit efficient compression schemes based on binary vector quantization, applied to the bitplanes of any monochrome or color image. Encryption is also naturally included using these codebooks. Natural images would require less than 0.5 bits per pixel (bpp while the quality of the reconstructed images is comparable with traditional compression schemes. The proposed scheme is attractive for low power, sensor integrated applications.

  19. The FBI compression standard for digitized fingerprint images

    Energy Technology Data Exchange (ETDEWEB)

    Brislawn, C.M.; Bradley, J.N. [Los Alamos National Lab., NM (United States); Onyshczak, R.J. [National Inst. of Standards and Technology, Gaithersburg, MD (United States); Hopper, T. [Federal Bureau of Investigation, Washington, DC (United States)

    1996-10-01

    The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the current status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.

  20. Image Compression Based On Wavelet, Polynomial and Quadtree

    Directory of Open Access Journals (Sweden)

    Bushra A. SULTAN

    2011-01-01

    Full Text Available In this paper a simple and fast image compression scheme is proposed, it is based on using wavelet transform to decompose the image signal and then using polynomial approximation to prune the smoothing component of the image band. The architect of proposed coding scheme is high synthetic where the error produced due to polynomial approximation in addition to the detail sub-band data are coded using both quantization and Quadtree spatial coding. As a last stage of the encoding process shift encoding is used as a simple and efficient entropy encoder to compress the outcomes of the previous stage.The test results indicate that the proposed system can produce a promising compression performance while preserving the image quality level.

  1. Wavelets: Applications to Image Compression-I

    Indian Academy of Sciences (India)

    form (OWl). Digital imaging has had an enormous impact on ... Digital images have become an important source of in- ... media applications and is the focus of this article. ..... Theory and Applications, Pearson Education InC., Delhi, India, 2000.

  2. Biomedical Imaging Modality Classification Using Combined Visual Features and Textual Terms

    Directory of Open Access Journals (Sweden)

    Xian-Hua Han

    2011-01-01

    extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

  3. Compton scatter imaging: A promising modality for image guidance in lung stereotactic body radiation therapy.

    Science.gov (United States)

    Redler, Gage; Jones, Kevin C; Templeton, Alistair; Bernard, Damian; Turian, Julius; Chu, James C H

    2018-03-01

    Lung stereotactic body radiation therapy (SBRT) requires delivering large radiation doses with millimeter accuracy, making image guidance essential. An approach to forming images of patient anatomy from Compton-scattered photons during lung SBRT is presented. To investigate the potential of scatter imaging, a pinhole collimator and flat-panel detector are used for spatial localization and detection of photons scattered during external beam therapy using lung SBRT treatment conditions (6 MV FFF beam). MCNP Monte Carlo software is used to develop a model to simulate scatter images. This model is validated by comparing experimental and simulated phantom images. Patient scatter images are then simulated from 4DCT data. Experimental lung tumor phantom images have sufficient contrast-to-noise to visualize the tumor with as few as 10 MU (0.5 s temporal resolution). The relative signal intensity from objects of different composition as well as lung tumor contrast for simulated phantom images agree quantitatively with experimental images, thus validating the Monte Carlo model. Scatter images are shown to display high contrast between different materials (lung, water, bone). Simulated patient images show superior (~double) tumor contrast compared to MV transmission images. Compton scatter imaging is a promising modality for directly imaging patient anatomy during treatment without additional radiation, and it has the potential to complement existing technologies and aid tumor tracking and lung SBRT image guidance. © 2018 American Association of Physicists in Medicine.

  4. Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

    Science.gov (United States)

    Huang, Yawen; Shao, Ling; Frangi, Alejandro F

    2018-03-01

    Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

  5. High speed fluorescence imaging with compressed ultrafast photography

    Science.gov (United States)

    Thompson, J. V.; Mason, J. D.; Beier, H. T.; Bixler, J. N.

    2017-02-01

    Fluorescent lifetime imaging is an optical technique that facilitates imaging molecular interactions and cellular functions. Because the excited lifetime of a fluorophore is sensitive to its local microenvironment,1, 2 measurement of fluorescent lifetimes can be used to accurately detect regional changes in temperature, pH, and ion concentration. However, typical state of the art fluorescent lifetime methods are severely limited when it comes to acquisition time (on the order of seconds to minutes) and video rate imaging. Here we show that compressed ultrafast photography (CUP) can be used in conjunction with fluorescent lifetime imaging to overcome these acquisition rate limitations. Frame rates up to one hundred billion frames per second have been demonstrated with compressed ultrafast photography using a streak camera.3 These rates are achieved by encoding time in the spatial direction with a pseudo-random binary pattern. The time domain information is then reconstructed using a compressed sensing algorithm, resulting in a cube of data (x,y,t) for each readout image. Thus, application of compressed ultrafast photography will allow us to acquire an entire fluorescent lifetime image with a single laser pulse. Using a streak camera with a high-speed CMOS camera, acquisition rates of 100 frames per second can be achieved, which will significantly enhance our ability to quantitatively measure complex biological events with high spatial and temporal resolution. In particular, we will demonstrate the ability of this technique to do single-shot fluorescent lifetime imaging of cells and microspheres.

  6. Image compression using moving average histogram and RBF network

    International Nuclear Information System (INIS)

    Khowaja, S.; Ismaili, I.A.

    2015-01-01

    Modernization and Globalization have made the multimedia technology as one of the fastest growing field in recent times but optimal use of bandwidth and storage has been one of the topics which attract the research community to work on. Considering that images have a lion share in multimedia communication, efficient image compression technique has become the basic need for optimal use of bandwidth and space. This paper proposes a novel method for image compression based on fusion of moving average histogram and RBF (Radial Basis Function). Proposed technique employs the concept of reducing color intensity levels using moving average histogram technique followed by the correction of color intensity levels using RBF networks at reconstruction phase. Existing methods have used low resolution images for the testing purpose but the proposed method has been tested on various image resolutions to have a clear assessment of the said technique. The proposed method have been tested on 35 images with varying resolution and have been compared with the existing algorithms in terms of CR (Compression Ratio), MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio), computational complexity. The outcome shows that the proposed methodology is a better trade off technique in terms of compression ratio, PSNR which determines the quality of the image and computational complexity. (author)

  7. Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

    Science.gov (United States)

    Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

    2017-04-01

    Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

  8. Hyperspectral image compressing using wavelet-based method

    Science.gov (United States)

    Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng

    2017-10-01

    Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

  9. Effect of Image Linearization on Normalized Compression Distance

    Science.gov (United States)

    Mortensen, Jonathan; Wu, Jia Jie; Furst, Jacob; Rogers, John; Raicu, Daniela

    Normalized Information Distance, based on Kolmogorov complexity, is an emerging metric for image similarity. It is approximated by the Normalized Compression Distance (NCD) which generates the relative distance between two strings by using standard compression algorithms to compare linear strings of information. This relative distance quantifies the degree of similarity between the two objects. NCD has been shown to measure similarity effectively on information which is already a string: genomic string comparisons have created accurate phylogeny trees and NCD has also been used to classify music. Currently, to find a similarity measure using NCD for images, the images must first be linearized into a string, and then compared. To understand how linearization of a 2D image affects the similarity measure, we perform four types of linearization on a subset of the Corel image database and compare each for a variety of image transformations. Our experiment shows that different linearization techniques produce statistically significant differences in NCD for identical spatial transformations.

  10. Contributions in compression of 3D medical images and 2D images; Contributions en compression d'images medicales 3D et d'images naturelles 2D

    Energy Technology Data Exchange (ETDEWEB)

    Gaudeau, Y

    2006-12-15

    The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

  11. Sparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.

    Science.gov (United States)

    She, Huajun; Chen, Rong-Rong; Liang, Dong; DiBella, Edward V R; Ying, Leslie

    2014-02-01

    To develop a sensitivity-based parallel imaging reconstruction method to reconstruct iteratively both the coil sensitivities and MR image simultaneously based on their prior information. Parallel magnetic resonance imaging reconstruction problem can be formulated as a multichannel sampling problem where solutions are sought analytically. However, the channel functions given by the coil sensitivities in parallel imaging are not known exactly and the estimation error usually leads to artifacts. In this study, we propose a new reconstruction algorithm, termed Sparse BLind Iterative Parallel, for blind iterative parallel imaging reconstruction using compressed sensing. The proposed algorithm reconstructs both the sensitivity functions and the image simultaneously from undersampled data. It enforces the sparseness constraint in the image as done in compressed sensing, but is different from compressed sensing in that the sensing matrix is unknown and additional constraint is enforced on the sensitivities as well. Both phantom and in vivo imaging experiments were carried out with retrospective undersampling to evaluate the performance of the proposed method. Experiments show improvement in Sparse BLind Iterative Parallel reconstruction when compared with Sparse SENSE, JSENSE, IRGN-TV, and L1-SPIRiT reconstructions with the same number of measurements. The proposed Sparse BLind Iterative Parallel algorithm reduces the reconstruction errors when compared to the state-of-the-art parallel imaging methods. Copyright © 2013 Wiley Periodicals, Inc.

  12. Dual-Modality Prostate Imaging with PET and Transrectal Ultrasound

    Science.gov (United States)

    2011-09-01

    Downloaded on April 07,2010 at 23:12:26 UTC from IEEE Xplore . Restrictions apply. HUBER et al.: MULTI-MODALITY PHANTOM DEVELOPMENT 2723 As soon as...allow Authorized licensed use limited to: Lawrence Berkeley National Laboratory. Downloaded on April 07,2010 at 23:12:26 UTC from IEEE Xplore ...April 07,2010 at 23:12:26 UTC from IEEE Xplore . Restrictions apply. HUBER et al.: MULTI-MODALITY PHANTOM DEVELOPMENT 2725 Fig. 3. Reconstructed

  13. MR imaging of recurrent hyperparathyroidism in comparison with other imaging modalities

    International Nuclear Information System (INIS)

    Auffermann, W.; Thurnher, S.; Okerland, M.; Levin, K.; Gooding, G.W.; Clark, O.H.; Higgins, C.B.

    1987-01-01

    Thirty patients with recurrent hyperparathyroidism were evaluated with MR imaging, performed using a saddle-shaped surface coil producing 5-mm sections with T1 and T2 weighting. Twenty-six and 22 of these patients also underwent T1-201 scintigraphy and high-resolution US, respectively. MR imaging accurately localized abnormal parathyroid glands in 75% evaluated prospectively and 86% retrospectively. Scintigraphy localized 64% prospectively and 72% retrospectively. US demonstrated 57% prospectively and 67% retrospectively. MR imaging showed three of four mediastinal adenomas evaluated prospectively retrospectively. There were two false-positive studies with MR imaging, two with scintigraphy, and one with US. Thus, MR imaging was the most effective imaging modality for parathyroid localization in recurrent hyperparathyroidism

  14. Radiation dose reduction and new image modalities development for interventional C-arm imaging system

    Science.gov (United States)

    Niu, Kai

    Cardiovascular disease and stroke are the leading health problems and causes of death in the US. Due to the minimally invasive nature of the evolution of image guided techniques, interventional radiological procedures are becoming more common and are preferred in treating many cardiovascular diseases and strokes. In addition, with the recent advances in hardware and device technology, the speed and efficacy of interventional treatment has significantly improved. This implies that more image modalities can be developed based on the current C-arm system and patients treated in interventional suites can potentially experience better health outcomes. However, during the treatment patients are irradiated with substantial amounts of ionizing radiation with a high dose rate (digital subtraction angiography (DSA) with 3muGy/frame and 3D cone beam CT image with 0.36muGy/frame for a Siemens Artis Zee biplane system) and/or a long irradiation time (a roadmapping image sequence can be as long as one hour during aneurysm embolization). As a result, the patient entrance dose is extremely high. Despite the fact that the radiation dose is already substantial, image quality is not always satisfactory. By default a temporal average is used in roadmapping images to overcome poor image quality, but this technique can result in motion blurred images. Therefore, reducing radiation dose while maintaining or even improving the image quality is an important area for continued research. This thesis is focused on improving the clinical applications of C-arm cone beam CT systems in two ways: (1) Improve the performance of current image modalities on the C-arm system. (2) Develop new image modalities based on the current system. To be more specific, the objectives are to reduce radiation dose for current modalities (e.g., DSA, fluoroscopy, roadmapping, and cone beam CT) and enable cone beam CT perfusion and time resolved cone beam CT angiography that can be used to diagnose and triage acute

  15. A Parallel Approach to Fractal Image Compression

    OpenAIRE

    Lubomir Dedera

    2004-01-01

    The paper deals with a parallel approach to coding and decoding algorithms in fractal image compressionand presents experimental results comparing sequential and parallel algorithms from the point of view of achieved bothcoding and decoding time and effectiveness of parallelization.

  16. View compensated compression of volume rendered images for remote visualization.

    Science.gov (United States)

    Lalgudi, Hariharan G; Marcellin, Michael W; Bilgin, Ali; Oh, Han; Nadar, Mariappan S

    2009-07-01

    Remote visualization of volumetric images has gained importance over the past few years in medical and industrial applications. Volume visualization is a computationally intensive process, often requiring hardware acceleration to achieve a real time viewing experience. One remote visualization model that can accomplish this would transmit rendered images from a server, based on viewpoint requests from a client. For constrained server-client bandwidth, an efficient compression scheme is vital for transmitting high quality rendered images. In this paper, we present a new view compensation scheme that utilizes the geometric relationship between viewpoints to exploit the correlation between successive rendered images. The proposed method obviates motion estimation between rendered images, enabling significant reduction to the complexity of a compressor. Additionally, the view compensation scheme, in conjunction with JPEG2000 performs better than AVC, the state of the art video compression standard.

  17. Development of information preserving data compression algorithm for CT images

    International Nuclear Information System (INIS)

    Kobayashi, Yoshio

    1989-01-01

    Although digital imaging techniques in radiology develop rapidly, problems arise in archival storage and communication of image data. This paper reports on a new information preserving data compression algorithm for computed tomographic (CT) images. This algorithm consists of the following five processes: 1. Pixels surrounding the human body showing CT values smaller than -900 H.U. are eliminated. 2. Each pixel is encoded by its numerical difference from its neighboring pixel along a matrix line. 3. Difference values are encoded by a newly designed code rather than the natural binary code. 4. Image data, obtained with the above process, are decomposed into bit planes. 5. The bit state transitions in each bit plane are encoded by run length coding. Using this new algorithm, the compression ratios of brain, chest, and abdomen CT images are 4.49, 4.34. and 4.40 respectively. (author)

  18. Sparse representations and compressive sensing for imaging and vision

    CERN Document Server

    Patel, Vishal M

    2013-01-01

    Compressed sensing or compressive sensing is a new concept in signal processing where one measures a small number of non-adaptive linear combinations of the signal.  These measurements are usually much smaller than the number of samples that define the signal.  From these small numbers of measurements, the signal is then reconstructed by non-linear procedure.  Compressed sensing has recently emerged as a powerful tool for efficiently processing data in non-traditional ways.  In this book, we highlight some of the key mathematical insights underlying sparse representation and compressed sensing and illustrate the role of these theories in classical vision, imaging and biometrics problems.

  19. A JPEG backward-compatible HDR image compression

    Science.gov (United States)

    Korshunov, Pavel; Ebrahimi, Touradj

    2012-10-01

    High Dynamic Range (HDR) imaging is expected to become one of the technologies that could shape next generation of consumer digital photography. Manufacturers are rolling out cameras and displays capable of capturing and rendering HDR images. The popularity and full public adoption of HDR content is however hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of Low Dynamic Range (LDR) displays that are unable to render HDR. To facilitate wide spread of HDR usage, the backward compatibility of HDR technology with commonly used legacy image storage, rendering, and compression is necessary. Although many tone-mapping algorithms were developed for generating viewable LDR images from HDR content, there is no consensus on which algorithm to use and under which conditions. This paper, via a series of subjective evaluations, demonstrates the dependency of perceived quality of the tone-mapped LDR images on environmental parameters and image content. Based on the results of subjective tests, it proposes to extend JPEG file format, as the most popular image format, in a backward compatible manner to also deal with HDR pictures. To this end, the paper provides an architecture to achieve such backward compatibility with JPEG and demonstrates efficiency of a simple implementation of this framework when compared to the state of the art HDR image compression.

  20. Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Multi-modality medical image fusion has more and more important applications in medical image analysisand understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fusemedical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusionresults when applying different selection rules and obtain optimum combination of fusion parameters.

  1. Efficient reconfigurable architectures for 3D medical image compression

    OpenAIRE

    Afandi, Ahmad

    2010-01-01

    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University. Recently, the more widespread use of three-dimensional (3-D) imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US) have generated a massive amount of volumetric data. These have provided an impetus to the development of other applications, in particular telemedicine and teleradiology. In thes...

  2. Distributed Source Coding Techniques for Lossless Compression of Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Barni Mauro

    2007-01-01

    Full Text Available This paper deals with the application of distributed source coding (DSC theory to remote sensing image compression. Although DSC exhibits a significant potential in many application fields, up till now the results obtained on real signals fall short of the theoretical bounds, and often impose additional system-level constraints. The objective of this paper is to assess the potential of DSC for lossless image compression carried out onboard a remote platform. We first provide a brief overview of DSC of correlated information sources. We then focus on onboard lossless image compression, and apply DSC techniques in order to reduce the complexity of the onboard encoder, at the expense of the decoder's, by exploiting the correlation of different bands of a hyperspectral dataset. Specifically, we propose two different compression schemes, one based on powerful binary error-correcting codes employed as source codes, and one based on simpler multilevel coset codes. The performance of both schemes is evaluated on a few AVIRIS scenes, and is compared with other state-of-the-art 2D and 3D coders. Both schemes turn out to achieve competitive compression performance, and one of them also has reduced complexity. Based on these results, we highlight the main issues that are still to be solved to further improve the performance of DSC-based remote sensing systems.

  3. Fractal Image Compression Based on High Entropy Values Technique

    Directory of Open Access Journals (Sweden)

    Douaa Younis Abbaas

    2018-04-01

    Full Text Available There are many attempts tried to improve the encoding stage of FIC because it consumed time. These attempts worked by reducing size of the search pool for pair range-domain matching but most of them led to get a bad quality, or a lower compression ratio of reconstructed image. This paper aims to present a method to improve performance of the full search algorithm by combining FIC (lossy compression and another lossless technique (in this case entropy coding is used. The entropy technique will reduce size of the domain pool (i. e., number of domain blocks based on the entropy value of each range block and domain block and then comparing the results of full search algorithm and proposed algorithm based on entropy technique to see each of which give best results (such as reduced the encoding time with acceptable values in both compression quali-ty parameters which are C. R (Compression Ratio and PSNR (Image Quality. The experimental results of the proposed algorithm proven that using the proposed entropy technique reduces the encoding time while keeping compression rates and reconstruction image quality good as soon as possible.

  4. A novel high-frequency encoding algorithm for image compression

    Science.gov (United States)

    Siddeq, Mohammed M.; Rodrigues, Marcos A.

    2017-12-01

    In this paper, a new method for image compression is proposed whose quality is demonstrated through accurate 3D reconstruction from 2D images. The method is based on the discrete cosine transform (DCT) together with a high-frequency minimization encoding algorithm at compression stage and a new concurrent binary search algorithm at decompression stage. The proposed compression method consists of five main steps: (1) divide the image into blocks and apply DCT to each block; (2) apply a high-frequency minimization method to the AC-coefficients reducing each block by 2/3 resulting in a minimized array; (3) build a look up table of probability data to enable the recovery of the original high frequencies at decompression stage; (4) apply a delta or differential operator to the list of DC-components; and (5) apply arithmetic encoding to the outputs of steps (2) and (4). At decompression stage, the look up table and the concurrent binary search algorithm are used to reconstruct all high-frequency AC-coefficients while the DC-components are decoded by reversing the arithmetic coding. Finally, the inverse DCT recovers the original image. We tested the technique by compressing and decompressing 2D images including images with structured light patterns for 3D reconstruction. The technique is compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results demonstrate that the proposed compression method is perceptually superior to JPEG with equivalent quality to JPEG2000. Concerning 3D surface reconstruction from images, it is demonstrated that the proposed method is superior to both JPEG and JPEG2000.

  5. Digital image sequence processing, compression, and analysis

    CERN Document Server

    Reed, Todd R

    2004-01-01

    IntroductionTodd R. ReedCONTENT-BASED IMAGE SEQUENCE REPRESENTATIONPedro M. Q. Aguiar, Radu S. Jasinschi, José M. F. Moura, andCharnchai PluempitiwiriyawejTHE COMPUTATION OF MOTIONChristoph Stiller, Sören Kammel, Jan Horn, and Thao DangMOTION ANALYSIS AND DISPLACEMENT ESTIMATION IN THE FREQUENCY DOMAINLuca Lucchese and Guido Maria CortelazzoQUALITY OF SERVICE ASSESSMENT IN NEW GENERATION WIRELESS VIDEO COMMUNICATIONSGaetano GiuntaERROR CONCEALMENT IN DIGITAL VIDEOFrancesco G.B. De NataleIMAGE SEQUENCE RESTORATION: A WIDER PERSPECTIVEAnil KokaramVIDEO SUMMARIZATIONCuneyt M. Taskiran and Edward

  6. A Review On Segmentation Based Image Compression Techniques

    Directory of Open Access Journals (Sweden)

    S.Thayammal

    2013-11-01

    Full Text Available Abstract -The storage and transmission of imagery become more challenging task in the current scenario of multimedia applications. Hence, an efficient compression scheme is highly essential for imagery, which reduces the requirement of storage medium and transmission bandwidth. Not only improvement in performance and also the compression techniques must converge quickly in order to apply them for real time applications. There are various algorithms have been done in image compression, but everyone has its own pros and cons. Here, an extensive analysis between existing methods is performed. Also, the use of existing works is highlighted, for developing the novel techniques which face the challenging task of image storage and transmission in multimedia applications.

  7. A Parallel Approach to Fractal Image Compression

    Directory of Open Access Journals (Sweden)

    Lubomir Dedera

    2004-01-01

    Full Text Available The paper deals with a parallel approach to coding and decoding algorithms in fractal image compressionand presents experimental results comparing sequential and parallel algorithms from the point of view of achieved bothcoding and decoding time and effectiveness of parallelization.

  8. Applications of Novel X-Ray Imaging Modalities in Food Science

    DEFF Research Database (Denmark)

    Nielsen, Mikkel Schou

    science for understanding and designing food products. In both of these aspects, X-ray imaging methods such as radiography and computed tomography provide a non-destructive solution. However, since the conventional attenuation-based modality suers from poor contrast in soft matter materials, modalities...... with improved contrast are needed. Two possible candidates in this regard are the novel X-ray phase-contrast and X-ray dark-eld imaging modalities. The contrast in phase-contrast imaging is based on dierences in electron density which is especially useful for soft matter materials whereas dark-eld imaging....... Furthermore, the process of translating the image in image analysis was addressed. For improved handling of multimodal image data, a multivariate segmentation scheme of multimodal X-ray tomography data was implemented. Finally, quantitative data analysis was applied for treating the images. Quantitative...

  9. Subsurface Profile Mapping using 3-D Compressive Wave Imaging

    Directory of Open Access Journals (Sweden)

    Hazreek Z A M

    2017-01-01

    Full Text Available Geotechnical site investigation related to subsurface profile mapping was commonly performed to provide valuable data for design and construction stage based on conventional drilling techniques. From past experience, drilling techniques particularly using borehole method suffer from limitations related to expensive, time consuming and limited data coverage. Hence, this study performs subsurface profile mapping using 3-D compressive wave imaging in order to minimize those conventional method constraints. Field measurement and data analysis of compressive wave (p-wave, vp was performed using seismic refraction survey (ABEM Terraloc MK 8, 7 kg of sledgehammer and 24 units of vertical geophone and OPTIM (SeisOpt@Picker & SeisOpt@2D software respectively. Then, 3-D compressive wave distribution of subsurface studied was obtained using analysis of SURFER software. Based on 3-D compressive wave image analyzed, it was found that subsurface profile studied consist of three main layers representing top soil (vp = 376 – 600 m/s, weathered material (vp = 900 – 2600 m/s and bedrock (vp > 3000 m/s. Thickness of each layer was varied from 0 – 2 m (first layer, 2 – 20 m (second layer and 20 m and over (third layer. Moreover, groundwater (vp = 1400 – 1600 m/s starts to be detected at 2.0 m depth from ground surface. This study has demonstrated that geotechnical site investigation data related to subsurface profiling was applicable to be obtained using 3-D compressive wave imaging. Furthermore, 3-D compressive wave imaging was performed based on non destructive principle in ground exploration thus consider economic, less time, large data coverage and sustainable to our environment.

  10. A new modified fast fractal image compression algorithm

    DEFF Research Database (Denmark)

    Salarian, Mehdi; Nadernejad, Ehsan; MiarNaimi, Hossein

    2013-01-01

    In this paper, a new fractal image compression algorithm is proposed, in which the time of the encoding process is considerably reduced. The algorithm exploits a domain pool reduction approach, along with the use of innovative predefined values for contrast scaling factor, S, instead of searching...

  11. Polarimetric and Indoor Imaging Fusion Based on Compressive Sensing

    Science.gov (United States)

    2013-04-01

    34 in Proc. IEEE Radar Conf, Rome, Italy , May 2008. [17] M. G. Amin, F. Ahmad, W. Zhang, "A compressive sensing approach to moving target... Ferrara , J. Jackson, and M. Stuff, "Three-dimensional sparse-aperture moving-target imaging," in Proc. SPIE, vol. 6970, 2008. [43] M. Skolnik (Ed

  12. 32Still Image Compression Algorithm Based on Directional Filter Banks

    OpenAIRE

    Chunling Yang; Duanwu Cao; Li Ma

    2010-01-01

    Hybrid wavelet and directional filter banks (HWD) is an effective multi-scale geometrical analysis method. Compared to wavelet transform, it can better capture the directional information of images. But the ringing artifact, which is caused by the coefficient quantization in transform domain, is the biggest drawback of image compression algorithms in HWD domain. In this paper, by researching on the relationship between directional decomposition and ringing artifact, an improved decomposition ...

  13. Fast algorithm for exploring and compressing of large hyperspectral images

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    2011-01-01

    A new method for calculation of latent variable space for exploratory analysis and dimension reduction of large hyperspectral images is proposed. The method is based on significant downsampling of image pixels with preservation of pixels’ structure in feature (variable) space. To achieve this, in...... can be used first of all for fast compression of large data arrays with principal component analysis or similar projection techniques....

  14. Spectrally Adaptable Compressive Sensing Imaging System

    Science.gov (United States)

    2014-05-01

    capture the hyperspectral scene. Several simulations and experimental measurements demonstrate the benefits of the new discretization model. 11...apertures are used sequentially to capture the hyperspectral scene. Several simulations and experimental measurements demonstrate the benefits of the new...with our DMD-SSI setup. Figure 5.22(a) shows the imaging target used in this experiment, which is a red chili pepper with a green stem. Figure 5.22(b

  15. Facial Image Compression Based on Structured Codebooks in Overcomplete Domain

    Directory of Open Access Journals (Sweden)

    Vila-Forcén JE

    2006-01-01

    Full Text Available We advocate facial image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: image compression is considered from the position of source coding with side information and, contrarily to the existing scenarios where the side information is given explicitly; the side information is created based on a deterministic approximation of the local image features. We consider an image in the overcomplete transform domain as a realization of a random source with a structured codebook of symbols where each symbol represents a particular edge shape. Due to the partial availability of the side information at both encoder and decoder, we treat our problem as a modification of the Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available at the decoder. Finally, the paper presents a practical image compression algorithm for facial images based on our concept that demonstrates the superior performance in the very-low-bit-rate regime.

  16. Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

    Science.gov (United States)

    Sturgeon, Gregory M; Kiarashi, Nooshin; Lo, Joseph Y; Samei, E; Segars, W P

    2016-05-01

    The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging. This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast. The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts. The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging

  17. Image Quality Assessment of JPEG Compressed Mars Science Laboratory Mastcam Images using Convolutional Neural Networks

    Science.gov (United States)

    Kerner, H. R.; Bell, J. F., III; Ben Amor, H.

    2017-12-01

    The Mastcam color imaging system on the Mars Science Laboratory Curiosity rover acquires images within Gale crater for a variety of geologic and atmospheric studies. Images are often JPEG compressed before being downlinked to Earth. While critical for transmitting images on a low-bandwidth connection, this compression can result in image artifacts most noticeable as anomalous brightness or color changes within or near JPEG compression block boundaries. In images with significant high-frequency detail (e.g., in regions showing fine layering or lamination in sedimentary rocks), the image might need to be re-transmitted losslessly to enable accurate scientific interpretation of the data. The process of identifying which images have been adversely affected by compression artifacts is performed manually by the Mastcam science team, costing significant expert human time. To streamline the tedious process of identifying which images might need to be re-transmitted, we present an input-efficient neural network solution for predicting the perceived quality of a compressed Mastcam image. Most neural network solutions require large amounts of hand-labeled training data for the model to learn the target mapping between input (e.g. distorted images) and output (e.g. quality assessment). We propose an automatic labeling method using joint entropy between a compressed and uncompressed image to avoid the need for domain experts to label thousands of training examples by hand. We use automatically labeled data to train a convolutional neural network to estimate the probability that a Mastcam user would find the quality of a given compressed image acceptable for science analysis. We tested our model on a variety of Mastcam images and found that the proposed method correlates well with image quality perception by science team members. When assisted by our proposed method, we estimate that a Mastcam investigator could reduce the time spent reviewing images by a minimum of 70%.

  18. Optical Acquisition, Image and Data Compression

    Science.gov (United States)

    1988-07-30

    It is from problems where the syntactic method is a suitable this pattern vector that one starts the analysis and approach are fingerprint ...reference axes. FiG. 3. (a) Texture of French canvas ; (b) HT of a block of Fig. 3a: (c) HT of a block of Fig. 3a with preprocessing for line thinning...the p-0 (HT) plane as it will appear in the following illustrations. Figure 3a shows the texture image of French canvas (Brodatz’s plate No. 20

  19. Evaluation of registration strategies for multi-modality images of rat brain slices

    International Nuclear Information System (INIS)

    Palm, Christoph; Vieten, Andrea; Salber, Dagmar; Pietrzyk, Uwe

    2009-01-01

    In neuroscience, small-animal studies frequently involve dealing with series of images from multiple modalities such as histology and autoradiography. The consistent and bias-free restacking of multi-modality image series is obligatory as a starting point for subsequent non-rigid registration procedures and for quantitative comparisons with positron emission tomography (PET) and other in vivo data. Up to now, consistency between 2D slices without cross validation using an inherent 3D modality is frequently presumed to be close to the true morphology due to the smooth appearance of the contours of anatomical structures. However, in multi-modality stacks consistency is difficult to assess. In this work, consistency is defined in terms of smoothness of neighboring slices within a single modality and between different modalities. Registration bias denotes the distortion of the registered stack in comparison to the true 3D morphology and shape. Based on these metrics, different restacking strategies of multi-modality rat brain slices are experimentally evaluated. Experiments based on MRI-simulated and real dual-tracer autoradiograms reveal a clear bias of the restacked volume despite quantitatively high consistency and qualitatively smooth brain structures. However, different registration strategies yield different inter-consistency metrics. If no genuine 3D modality is available, the use of the so-called SOP (slice-order preferred) or MOSOP (modality-and-slice-order preferred) strategy is recommended.

  20. Reevaluation of JPEG image compression to digitalized gastrointestinal endoscopic color images: a pilot study

    Science.gov (United States)

    Kim, Christopher Y.

    1999-05-01

    Endoscopic images p lay an important role in describing many gastrointestinal (GI) disorders. The field of radiology has been on the leading edge of creating, archiving and transmitting digital images. With the advent of digital videoendoscopy, endoscopists now have the ability to generate images for storage and transmission. X-rays can be compressed 30-40X without appreciable decline in quality. We reported results of a pilot study using JPEG compression of 24-bit color endoscopic images. For that study, the result indicated that adequate compression ratios vary according to the lesion and that images could be compressed to between 31- and 99-fold smaller than the original size without an appreciable decline in quality. The purpose of this study was to expand upon the methodology of the previous sty with an eye towards application for the WWW, a medium which would expand both clinical and educational purposes of color medical imags. The results indicate that endoscopists are able to tolerate very significant compression of endoscopic images without loss of clinical image quality. This finding suggests that even 1 MB color images can be compressed to well under 30KB, which is considered a maximal tolerable image size for downloading on the WWW.

  1. Optimized nonorthogonal transforms for image compression.

    Science.gov (United States)

    Guleryuz, O G; Orchard, M T

    1997-01-01

    The transform coding of images is analyzed from a common standpoint in order to generate a framework for the design of optimal transforms. It is argued that all transform coders are alike in the way they manipulate the data structure formed by transform coefficients. A general energy compaction measure is proposed to generate optimized transforms with desirable characteristics particularly suited to the simple transform coding operation of scalar quantization and entropy coding. It is shown that the optimal linear decoder (inverse transform) must be an optimal linear estimator, independent of the structure of the transform generating the coefficients. A formulation that sequentially optimizes the transforms is presented, and design equations and algorithms for its computation provided. The properties of the resulting transform systems are investigated. In particular, it is shown that the resulting basis are nonorthogonal and complete, producing energy compaction optimized, decorrelated transform coefficients. Quantization issues related to nonorthogonal expansion coefficients are addressed with a simple, efficient algorithm. Two implementations are discussed, and image coding examples are given. It is shown that the proposed design framework results in systems with superior energy compaction properties and excellent coding results.

  2. Lossless compression of multispectral images using spectral information

    Science.gov (United States)

    Ma, Long; Shi, Zelin; Tang, Xusheng

    2009-10-01

    Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

  3. Videos and images from 25 years of teaching compressible flow

    Science.gov (United States)

    Settles, Gary

    2008-11-01

    Compressible flow is a very visual topic due to refractive optical flow visualization and the public fascination with high-speed flight. Films, video clips, and many images are available to convey this in the classroom. An overview of this material is given and selected examples are shown, drawn from educational films, the movies, television, etc., and accumulated over 25 years of teaching basic and advanced compressible-flow courses. The impact of copyright protection and the doctrine of fair use is also discussed.

  4. Multi-Modal Curriculum Learning for Semi-Supervised Image Classification.

    Science.gov (United States)

    Gong, Chen; Tao, Dacheng; Maybank, Stephen J; Liu, Wei; Kang, Guoliang; Yang, Jie

    2016-07-01

    Semi-supervised image classification aims to classify a large quantity of unlabeled images by typically harnessing scarce labeled images. Existing semi-supervised methods often suffer from inadequate classification accuracy when encountering difficult yet critical images, such as outliers, because they treat all unlabeled images equally and conduct classifications in an imperfectly ordered sequence. In this paper, we employ the curriculum learning methodology by investigating the difficulty of classifying every unlabeled image. The reliability and the discriminability of these unlabeled images are particularly investigated for evaluating their difficulty. As a result, an optimized image sequence is generated during the iterative propagations, and the unlabeled images are logically classified from simple to difficult. Furthermore, since images are usually characterized by multiple visual feature descriptors, we associate each kind of features with a teacher, and design a multi-modal curriculum learning (MMCL) strategy to integrate the information from different feature modalities. In each propagation, each teacher analyzes the difficulties of the currently unlabeled images from its own modality viewpoint. A consensus is subsequently reached among all the teachers, determining the currently simplest images (i.e., a curriculum), which are to be reliably classified by the multi-modal learner. This well-organized propagation process leveraging multiple teachers and one learner enables our MMCL to outperform five state-of-the-art methods on eight popular image data sets.

  5. A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

    Directory of Open Access Journals (Sweden)

    Lu Guo

    Full Text Available To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors.A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT and tri-modality (MRI/CT/PET image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV, the average distance between surface and centroid (ADSC, and the local standard deviation (SDlocal. Analysis of COV was also performed to evaluate intra-observer volume variation.The inter-observer variation analysis showed that, the mean COV was 0.14(± 0.09 and 0.07(± 0.01 for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05 with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm and patient 3 (from 0.42 cm to 0.36 cm with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00 with the tri-modality method as compared with using the dual-modality method.With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy.

  6. Development and assessment of compression technique for medical images using neural network. I. Assessment of lossless compression

    International Nuclear Information System (INIS)

    Fukatsu, Hiroshi

    2007-01-01

    This paper describes assessment of the lossless compression of a new efficient compression technique (JIS system) using neural network that the author and co-workers have recently developed. At first, theory is explained for encoding and decoding the data. Assessment is done on 55 images each of chest digital roentgenography, digital mammography, 64-row multi-slice CT, 1.5 Tesla MRI, positron emission tomography (PET) and digital subtraction angiography, which are lossless-compressed by the present JIS system to see the compression rate and loss. For comparison, those data are also JPEG lossless-compressed. Personal computer (PC) is an Apple MacBook Pro with configuration of Boot Camp for Windows environment. The present JIS system is found to have a more than 4 times higher efficiency than the usual compressions which compressing the file volume to only 1/11 in average, and thus to be importantly responsible to the increasing medical imaging data. (R.T.)

  7. Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

    Science.gov (United States)

    Cascianelli, Silvia; Scialpi, Michele; Amici, Serena; Forini, Nevio; Minestrini, Matteo; Fravolini, Mario Luca; Sinzinger, Helmut; Schillaci, Orazio; Palumbo, Barbara

    2017-01-01

    Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

  8. IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities)

    National Research Council Canada - National Science Library

    Hong, Waun Ki; Herbst, Roy

    2006-01-01

    .... These projects combine targeted approaches using molecular and imaging techniques to validate activity against a target and monitor response using imaging modalities specific to the receptor using...

  9. IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities)

    National Research Council Canada - National Science Library

    Hong, Waun K; Herbst, Roy

    2008-01-01

    .... These projects combine targeted approaches using molecular and imaging techniques to validate activity against a target and monitor response using imaging modalities specific to the receptor using...

  10. IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities)

    National Research Council Canada - National Science Library

    Hong, Waun K; Herbst, Roy

    2007-01-01

    .... These projects combine targeted approaches using molecular and imaging techniques to validate activity against a target and monitor response using imaging modalities specific to the receptor using...

  11. Spatial compression algorithm for the analysis of very large multivariate images

    Science.gov (United States)

    Keenan, Michael R [Albuquerque, NM

    2008-07-15

    A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

  12. Optimization of compressive 4D-spatio-spectral snapshot imaging

    Science.gov (United States)

    Zhao, Xia; Feng, Weiyi; Lin, Lihua; Su, Wu; Xu, Guoqing

    2017-10-01

    In this paper, a modified 3D computational reconstruction method in the compressive 4D-spectro-volumetric snapshot imaging system is proposed for better sensing spectral information of 3D objects. In the design of the imaging system, a microlens array (MLA) is used to obtain a set of multi-view elemental images (EIs) of the 3D scenes. Then, these elemental images with one dimensional spectral information and different perspectives are captured by the coded aperture snapshot spectral imager (CASSI) which can sense the spectral data cube onto a compressive 2D measurement image. Finally, the depth images of 3D objects at arbitrary depths, like a focal stack, are computed by inversely mapping the elemental images according to geometrical optics. With the spectral estimation algorithm, the spectral information of 3D objects is also reconstructed. Using a shifted translation matrix, the contrast of the reconstruction result is further enhanced. Numerical simulation results verify the performance of the proposed method. The system can obtain both 3D spatial information and spectral data on 3D objects using only one single snapshot, which is valuable in the agricultural harvesting robots and other 3D dynamic scenes.

  13. Molecular imaging needles: dual-modality optical coherence tomography and fluorescence imaging of labeled antibodies deep in tissue

    Science.gov (United States)

    Scolaro, Loretta; Lorenser, Dirk; Madore, Wendy-Julie; Kirk, Rodney W.; Kramer, Anne S.; Yeoh, George C.; Godbout, Nicolas; Sampson, David D.; Boudoux, Caroline; McLaughlin, Robert A.

    2015-01-01

    Molecular imaging using optical techniques provides insight into disease at the cellular level. In this paper, we report on a novel dual-modality probe capable of performing molecular imaging by combining simultaneous three-dimensional optical coherence tomography (OCT) and two-dimensional fluorescence imaging in a hypodermic needle. The probe, referred to as a molecular imaging (MI) needle, may be inserted tens of millimeters into tissue. The MI needle utilizes double-clad fiber to carry both imaging modalities, and is interfaced to a 1310-nm OCT system and a fluorescence imaging subsystem using an asymmetrical double-clad fiber coupler customized to achieve high fluorescence collection efficiency. We present, to the best of our knowledge, the first dual-modality OCT and fluorescence needle probe with sufficient sensitivity to image fluorescently labeled antibodies. Such probes enable high-resolution molecular imaging deep within tissue. PMID:26137379

  14. IMPROVED COMPRESSION OF XML FILES FOR FAST IMAGE TRANSMISSION

    Directory of Open Access Journals (Sweden)

    S. Manimurugan

    2011-02-01

    Full Text Available The eXtensible Markup Language (XML is a format that is widely used as a tool for data exchange and storage. It is being increasingly used in secure transmission of image data over wireless network and World Wide Web. Verbose in nature, XML files can be tens of megabytes long. Thus, to reduce their size and to allow faster transmission, compression becomes vital. Several general purpose compression tools have been proposed without satisfactory results. This paper proposes a novel technique using modified BWT for compressing XML files in a lossless fashion. The experimental results show that the performance of the proposed technique outperforms both general purpose and XML-specific compressors.

  15. Bi-level image compression with tree coding

    DEFF Research Database (Denmark)

    Martins, Bo; Forchhammer, Søren

    1996-01-01

    Presently, tree coders are the best bi-level image coders. The current ISO standard, JBIG, is a good example. By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code. Three general-purpose coders...... are constructed by this principle. A multi-pass free tree coding scheme produces superior compression results for all test images. A multi-pass fast free template coding scheme produces much better results than JBIG for difficult images, such as halftonings. Rissanen's algorithm `Context' is presented in a new...

  16. Compression and Processing of Space Image Sequences of Northern Lights and Sprites

    DEFF Research Database (Denmark)

    Forchhammer, Søren Otto; Martins, Bo; Jensen, Ole Riis

    1999-01-01

    Compression of image sequences of auroral activity as northern lights and thunderstorms with sprites is investigated.......Compression of image sequences of auroral activity as northern lights and thunderstorms with sprites is investigated....

  17. Lossless Image Compression Based on Multiple-Tables Arithmetic Coding

    Directory of Open Access Journals (Sweden)

    Rung-Ching Chen

    2009-01-01

    Full Text Available This paper is intended to present a lossless image compression method based on multiple-tables arithmetic coding (MTAC method to encode a gray-level image f. First, the MTAC method employs a median edge detector (MED to reduce the entropy rate of f. The gray levels of two adjacent pixels in an image are usually similar. A base-switching transformation approach is then used to reduce the spatial redundancy of the image. The gray levels of some pixels in an image are more common than those of others. Finally, the arithmetic encoding method is applied to reduce the coding redundancy of the image. To promote high performance of the arithmetic encoding method, the MTAC method first classifies the data and then encodes each cluster of data using a distinct code table. The experimental results show that, in most cases, the MTAC method provides a higher efficiency in use of storage space than the lossless JPEG2000 does.

  18. REMOTELY SENSEDC IMAGE COMPRESSION BASED ON WAVELET TRANSFORM

    Directory of Open Access Journals (Sweden)

    Heung K. Lee

    1996-06-01

    Full Text Available In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR and classification capability.

  19. Optimum image compression rate maintaining diagnostic image quality of digital intraoral radiographs

    International Nuclear Information System (INIS)

    Song, Ju Seop; Koh, Kwang Joon

    2000-01-01

    The aims of the present study are to determine the optimum compression rate in terms of file size reduction and diagnostic quality of the images after compression and evaluate the transmission speed of original or each compressed images. The material consisted of 24 extracted human premolars and molars. The occlusal surfaces and proximal surfaces of the teeth had a clinical disease spectrum that ranged from sound to varying degrees of fissure discoloration and cavitation. The images from Digora system were exported in TIFF and the images from conventional intraoral film were scanned and digitalized in TIFF by Nikon SF-200 scanner(Nikon, Japan). And six compression factors were chosen and applied on the basis of the results from a pilot study. The total number of images to be assessed were 336. Three radiologists assessed the occlusal and proximal surfaces of the teeth with 5-rank scale. Finally diagnosed as either sound or carious lesion by one expert oral pathologist. And sensitivity and specificity and kappa value for diagnostic agreement was calculated. Also the area (Az) values under the ROC curve were calculated and paired t-test and oneway ANOVA test was performed. Thereafter, transmission time of the image files of the each compression level were compared with that of the original image files. No significant difference was found between original and the corresponding images up to 7% (1:14) compression ratio for both the occlusal and proximal caries (p<0.05). JPEG3 (1:14) image files are transmitted fast more than 10 times, maintained diagnostic information in image, compared with original image files. 1:14 compressed image file may be used instead of the original image and reduce storage needs and transmission time.

  20. Classifying magnetic resonance image modalities with convolutional neural networks

    Science.gov (United States)

    Remedios, Samuel; Pham, Dzung L.; Butman, John A.; Roy, Snehashis

    2018-02-01

    Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Many MR brain image processing techniques, such as tissue segmentation, require multiple MR contrasts as inputs, and each contrast is treated differently. Thus it is advantageous to automate the identification of image contrasts for various purposes, such as facilitating image processing pipelines, and managing and maintaining large databases via content-based image retrieval (CBIR). Most automated CBIR techniques focus on a two-step process: extracting features from data and classifying the image based on these features. We present a novel 3D deep convolutional neural network (CNN)- based method for MR image contrast classification. The proposed CNN automatically identifies the MR contrast of an input brain image volume. Specifically, we explored three classification problems: (1) identify T1-weighted (T1-w), T2-weighted (T2-w), and fluid-attenuated inversion recovery (FLAIR) contrasts, (2) identify pre vs postcontrast T1, (3) identify pre vs post-contrast FLAIR. A total of 3418 image volumes acquired from multiple sites and multiple scanners were used. To evaluate each task, the proposed model was trained on 2137 images and tested on the remaining 1281 images. Results showed that image volumes were correctly classified with 97.57% accuracy.

  1. Astronomical Image Compression Techniques Based on ACC and KLT Coder

    Directory of Open Access Journals (Sweden)

    J. Schindler

    2011-01-01

    Full Text Available This paper deals with a compression of image data in applications in astronomy. Astronomical images have typical specific properties — high grayscale bit depth, size, noise occurrence and special processing algorithms. They belong to the class of scientific images. Their processing and compression is quite different from the classical approach of multimedia image processing. The database of images from BOOTES (Burst Observer and Optical Transient Exploring System has been chosen as a source of the testing signal. BOOTES is a Czech-Spanish robotic telescope for observing AGN (active galactic nuclei and the optical transient of GRB (gamma ray bursts searching. This paper discusses an approach based on an analysis of statistical properties of image data. A comparison of two irrelevancy reduction methods is presented from a scientific (astrometric and photometric point of view. The first method is based on a statistical approach, using the Karhunen-Loeve transform (KLT with uniform quantization in the spectral domain. The second technique is derived from wavelet decomposition with adaptive selection of used prediction coefficients. Finally, the comparison of three redundancy reduction methods is discussed. Multimedia format JPEG2000 and HCOMPRESS, designed especially for astronomical images, are compared with the new Astronomical Context Coder (ACC coder based on adaptive median regression.

  2. EBLAST: an efficient high-compression image transformation 3. application to Internet image and video transmission

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.; Caimi, Frank M.

    2001-12-01

    A wide variety of digital image compression transforms developed for still imaging and broadcast video transmission are unsuitable for Internet video applications due to insufficient compression ratio, poor reconstruction fidelity, or excessive computational requirements. Examples include hierarchical transforms that require all, or large portion of, a source image to reside in memory at one time, transforms that induce significant locking effect at operationally salient compression ratios, and algorithms that require large amounts of floating-point computation. The latter constraint holds especially for video compression by small mobile imaging devices for transmission to, and compression on, platforms such as palmtop computers or personal digital assistants (PDAs). As Internet video requirements for frame rate and resolution increase to produce more detailed, less discontinuous motion sequences, a new class of compression transforms will be needed, especially for small memory models and displays such as those found on PDAs. In this, the third series of papers, we discuss the EBLAST compression transform and its application to Internet communication. Leading transforms for compression of Internet video and still imagery are reviewed and analyzed, including GIF, JPEG, AWIC (wavelet-based), wavelet packets, and SPIHT, whose performance is compared with EBLAST. Performance analysis criteria include time and space complexity and quality of the decompressed image. The latter is determined by rate-distortion data obtained from a database of realistic test images. Discussion also includes issues such as robustness of the compressed format to channel noise. EBLAST has been shown to perform superiorly to JPEG and, unlike current wavelet compression transforms, supports fast implementation on embedded processors with small memory models.

  3. Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

    Science.gov (United States)

    Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

    2018-04-01

    Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

  4. Compression of fingerprint data using the wavelet vector quantization image compression algorithm. 1992 progress report

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, J.N.; Brislawn, C.M.

    1992-04-11

    This report describes the development of a Wavelet Vector Quantization (WVQ) image compression algorithm for fingerprint raster files. The pertinent work was performed at Los Alamos National Laboratory for the Federal Bureau of Investigation. This document describes a previously-sent package of C-language source code, referred to as LAFPC, that performs the WVQ fingerprint compression and decompression tasks. The particulars of the WVQ algorithm and the associated design procedure are detailed elsewhere; the purpose of this document is to report the results of the design algorithm for the fingerprint application and to delineate the implementation issues that are incorporated in LAFPC. Special attention is paid to the computation of the wavelet transform, the fast search algorithm used for the VQ encoding, and the entropy coding procedure used in the transmission of the source symbols.

  5. Multi-dimensional medical images compressed and filtered with wavelets

    International Nuclear Information System (INIS)

    Boyen, H.; Reeth, F. van; Flerackers, E.

    2002-01-01

    Full text: Using the standard wavelet decomposition methods, multi-dimensional medical images can be compressed and filtered by repeating the wavelet-algorithm on 1D-signals in an extra loop per extra dimension. In the non-standard decomposition for multi-dimensional images the areas that must be zero-filled in case of band- or notch-filters are more complex than geometric areas such as rectangles or cubes. Adding an additional dimension in this algorithm until 4D (e.g. a 3D beating heart) increases the geometric complexity of those areas even more. The aim of our study was to calculate the boundaries of the formed complex geometric areas, so we can use the faster non-standard decomposition to compress and filter multi-dimensional medical images. Because a lot of 3D medical images taken by PET- or SPECT-cameras have only a few layers in the Z-dimension and compressing images in a dimension with a few voxels is usually not worthwhile, we provided a solution in which one can choose which dimensions will be compressed or filtered. With the proposal of non-standard decomposition on Daubechies' wavelets D2 to D20 by Steven Gollmer in 1992, 1D data can be compressed and filtered. Each additional level works only on the smoothed data, so the transformation-time halves per extra level. Zero-filling a well-defined area alter the wavelet-transform and then performing the inverse transform will do the filtering. To be capable to compress and filter up to 4D-Images with the faster non-standard wavelet decomposition method, we have investigated a new method for calculating the boundaries of the areas which must be zero-filled in case of filtering. This is especially true for band- and notch filtering. Contrary to the standard decomposition method, the areas are no longer rectangles in 2D or cubes in 3D or a row of cubes in 4D: they are rectangles expanded with a half-sized rectangle in the other direction for 2D, cubes expanded with half cubes in one and quarter cubes in the

  6. Image interpolation used in three-dimensional range data compression.

    Science.gov (United States)

    Zhang, Shaoze; Zhang, Jianqi; Huang, Xi; Liu, Delian

    2016-05-20

    Advances in the field of three-dimensional (3D) scanning have made the acquisition of 3D range data easier and easier. However, with the large size of 3D range data comes the challenge of storing and transmitting it. To address this challenge, this paper presents a framework to further compress 3D range data using image interpolation. We first use a virtual fringe-projection system to store 3D range data as images, and then apply the interpolation algorithm to the images to reduce their resolution to further reduce the data size. When the 3D range data are needed, the low-resolution image is scaled up to its original resolution by applying the interpolation algorithm, and then the scaled-up image is decoded and the 3D range data are recovered according to the decoded result. Experimental results show that the proposed method could further reduce the data size while maintaining a low rate of error.

  7. Image acquisition system using on sensor compressed sampling technique

    Science.gov (United States)

    Gupta, Pravir Singh; Choi, Gwan Seong

    2018-01-01

    Advances in CMOS technology have made high-resolution image sensors possible. These image sensors pose significant challenges in terms of the amount of raw data generated, energy efficiency, and frame rate. This paper presents a design methodology for an imaging system and a simplified image sensor pixel design to be used in the system so that the compressed sensing (CS) technique can be implemented easily at the sensor level. This results in significant energy savings as it not only cuts the raw data rate but also reduces transistor count per pixel; decreases pixel size; increases fill factor; simplifies analog-to-digital converter, JPEG encoder, and JPEG decoder design; decreases wiring; and reduces the decoder size by half. Thus, CS has the potential to increase the resolution of image sensors for a given technology and die size while significantly decreasing the power consumption and design complexity. We show that it has potential to reduce power consumption by about 23% to 65%.

  8. Integrating imaging modalities: what makes sense from a workflow perspective?

    International Nuclear Information System (INIS)

    Schulthess, Gustav K. von; Burger, Cyrill

    2010-01-01

    From a workflow/cost perspective integrated imaging is not an obvious solution. An analysis of scanning costs as a function of system cost and relevant imaging times is presented. This analysis ignores potential clinical advantages of integrated imaging. An analysis comparing separate vs integrated imaging costs was performed by deriving pertinent equations and using reasonable cost numbers for imaging devices and systems, room and other variable costs. Integrated systems were divided into those sequentially and simultaneously. Sequential scanning can be done with two devices placed in a single or in two different scanning rooms. Graphs were derived which represent the cost difference between integrated imaging system options and their separate counterparts vs scanning time on one of the devices and cost ratio of an integrated system and its counterpart of separate devices. Integrated systems are favoured by the fact that patients have to be up- and downloaded only once. If imaging times become longer than patient changing times, imaging on separate devices is advantageous. An integrated imaging cost advantage is achieved if the integrated systems typically and overall cost three fourths or less of the separate systems. If PET imaging takes 15 min or less, PET/CT imaging costs less than separate PET and CT imaging, while this time is below 5 min for SPECT/CT. A two-room integrated system has the added advantage that patient download time is not cost relevant, when imaging times on the two devices differ by more than the patient download time. PET/CT scanning is a cost-effective implementation of an integrated system unlike most current SPECT/CT systems. Integration of two devices in two rooms by a shuttle seems the way how to make PET/MR cost-effective and may well also be a design option for SPECT/CT systems. (orig.)

  9. Efficient JPEG 2000 Image Compression Scheme for Multihop Wireless Networks

    Directory of Open Access Journals (Sweden)

    Halim Sghaier

    2011-08-01

    Full Text Available When using wireless sensor networks for real-time data transmission, some critical points should be considered. Restricted computational power, reduced memory, narrow bandwidth and energy supplied present strong limits in sensor nodes. Therefore, maximizing network lifetime and minimizing energy consumption are always optimization goals. To overcome the computation and energy limitation of individual sensor nodes during image transmission, an energy efficient image transport scheme is proposed, taking advantage of JPEG2000 still image compression standard using MATLAB and C from Jasper. JPEG2000 provides a practical set of features, not necessarily available in the previous standards. These features were achieved using techniques: the discrete wavelet transform (DWT, and embedded block coding with optimized truncation (EBCOT. Performance of the proposed image transport scheme is investigated with respect to image quality and energy consumption. Simulation results are presented and show that the proposed scheme optimizes network lifetime and reduces significantly the amount of required memory by analyzing the functional influence of each parameter of this distributed image compression algorithm.

  10. Spatial correlation genetic algorithm for fractal image compression

    International Nuclear Information System (INIS)

    Wu, M.-S.; Teng, W.-C.; Jeng, J.-H.; Hsieh, J.-G.

    2006-01-01

    Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match block in a large domain pool. In this paper, a spatial correlation genetic algorithm (SC-GA) is proposed to speed up the encoder. There are two stages for the SC-GA method. The first stage makes use of spatial correlations in images for both the domain pool and the range pool to exploit local optima. The second stage is operated on the whole image to explore more adequate similarities if the local optima are not satisfied. With the aid of spatial correlation in images, the encoding time is 1.5 times faster than that of traditional genetic algorithm method, while the quality of the retrieved image is almost the same. Moreover, about half of the matched blocks come from the correlated space, so fewer bits are required to represent the fractal transform and therefore the compression ratio is also improved

  11. Modeling decision-making in single- and multi-modal medical images

    Science.gov (United States)

    Canosa, R. L.; Baum, K. G.

    2009-02-01

    This research introduces a mode-specific model of visual saliency that can be used to highlight likely lesion locations and potential errors (false positives and false negatives) in single-mode PET and MRI images and multi-modal fused PET/MRI images. Fused-modality digital images are a relatively recent technological improvement in medical imaging; therefore, a novel component of this research is to characterize the perceptual response to these fused images. Three different fusion techniques were compared to single-mode displays in terms of observer error rates using synthetic human brain images generated from an anthropomorphic phantom. An eye-tracking experiment was performed with naÃve (non-radiologist) observers who viewed the single- and multi-modal images. The eye-tracking data allowed the errors to be classified into four categories: false positives, search errors (false negatives never fixated), recognition errors (false negatives fixated less than 350 milliseconds), and decision errors (false negatives fixated greater than 350 milliseconds). A saliency model consisting of a set of differentially weighted low-level feature maps is derived from the known error and ground truth locations extracted from a subset of the test images for each modality. The saliency model shows that lesion and error locations attract visual attention according to low-level image features such as color, luminance, and texture.

  12. Contributions in compression of 3D medical images and 2D images

    International Nuclear Information System (INIS)

    Gaudeau, Y.

    2006-12-01

    The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

  13. Magnetic resonance image compression using scalar-vector quantization

    Science.gov (United States)

    Mohsenian, Nader; Shahri, Homayoun

    1995-12-01

    A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.

  14. Performance evaluation of objective quality metrics for HDR image compression

    Science.gov (United States)

    Valenzise, Giuseppe; De Simone, Francesca; Lauga, Paul; Dufaux, Frederic

    2014-09-01

    Due to the much larger luminance and contrast characteristics of high dynamic range (HDR) images, well-known objective quality metrics, widely used for the assessment of low dynamic range (LDR) content, cannot be directly applied to HDR images in order to predict their perceptual fidelity. To overcome this limitation, advanced fidelity metrics, such as the HDR-VDP, have been proposed to accurately predict visually significant differences. However, their complex calibration may make them difficult to use in practice. A simpler approach consists in computing arithmetic or structural fidelity metrics, such as PSNR and SSIM, on perceptually encoded luminance values but the performance of quality prediction in this case has not been clearly studied. In this paper, we aim at providing a better comprehension of the limits and the potentialities of this approach, by means of a subjective study. We compare the performance of HDR-VDP to that of PSNR and SSIM computed on perceptually encoded luminance values, when considering compressed HDR images. Our results show that these simpler metrics can be effectively employed to assess image fidelity for applications such as HDR image compression.

  15. Multi-modal brain imaging software for guiding invasive treatment of epilepsy

    NARCIS (Netherlands)

    Ossenblok, P.P.W.; Marien, S.; Meesters, S.P.L.; Florack, L.M.J.; Hofman, P.; Schijns, O.E.M.G.; Colon, A.

    2017-01-01

    Purpose: The surgical treatment of patients with complex epilepsies is changing more and more from open, invasive surgery towards minimally invasive, image guided treatment. Multi-modal brain imaging procedures are developed to delineate preoperatively the region of the brain which is responsible

  16. Impact of Medical Therapy on Atheroma Volume Measured by Different Cardiovascular Imaging Modalities

    Directory of Open Access Journals (Sweden)

    Mohamad C. N. Sinno

    2010-01-01

    Full Text Available Atherosclerosis is a systemic disease that affects most vascular beds. The gold standard of atherosclerosis imaging has been invasive intravascular ultrasound (IVUS. Newer noninvasive imaging modalities like B-mode ultrasound, cardiac computed tomography (CT, positron emission tomography (PET, and magnetic resonance imaging (MRI have been used to assess these vascular territories with high accuracy and reproducibility. These imaging modalities have lately been used for the assessment of the atherosclerotic plaque and the response of its volume to several medical therapies used in the treatment of patients with cardiovascular disease. To study the impact of these medications on atheroma volume progression or regression, imaging modalities have been used on a serial basis providing a unique opportunity to monitor the effect these antiatherosclerotic strategies exert on plaque burden. As a result, studies incorporating serial IVUS imaging, quantitative coronary angiography (QCA, B-mode ultrasound, electron beam computed tomography (EBCT, and dynamic contrast-enhanced magnetic resonance imaging have all been used to evaluate the impact of therapeutic strategies that modify cholesterol and blood pressure on the progression/regression of atherosclerotic plaque. In this review, we intend to summarize the impact of different therapies aimed at halting the progression or even result in regression of atherosclerotic cardiovascular disease evaluated by different imaging modalities.

  17. Dual-modality imaging with a ultrasound-gamma device for oncology

    Science.gov (United States)

    Polito, C.; Pellegrini, R.; Cinti, M. N.; De Vincentis, G.; Lo Meo, S.; Fabbri, A.; Bennati, P.; Cencelli, V. Orsolini; Pani, R.

    2018-06-01

    Recently, dual-modality systems have been developed, aimed to correlate anatomical and functional information, improving disease localization and helping oncological or surgical treatments. Moreover, due to the growing interest in handheld detectors for preclinical trials or small animal imaging, in this work a new dual modality integrated device, based on a Ultrasounds probe and a small Field of View Single Photon Emission gamma camera, is proposed.

  18. Image Compression using Haar and Modified Haar Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Mohannad Abid Shehab Ahmed

    2013-04-01

    Full Text Available Efficient image compression approaches can provide the best solutions to the recent growth of the data intensive and multimedia based applications. As presented in many papers the Haar matrix–based methods and wavelet analysis can be used in various areas of image processing such as edge detection, preserving, smoothing or filtering. In this paper, color image compression analysis and synthesis based on Haar and modified Haar is presented. The standard Haar wavelet transformation with N=2 is composed of a sequence of low-pass and high-pass filters, known as a filter bank, the vertical and horizontal Haar filters are composed to construct four 2-dimensional filters, such filters applied directly to the image to speed up the implementation of the Haar wavelet transform. Modified Haar technique is studied and implemented for odd based numbers i.e. (N=3 & N=5 to generate many solution sets, these sets are tested using the energy function or numerical method to get the optimum one.The Haar transform is simple, efficient in memory usage due to high zero value spread (it can use sparse principle, and exactly reversible without the edge effects as compared to DCT (Discrete Cosine Transform. The implemented Matlab simulation results prove the effectiveness of DWT (Discrete Wave Transform algorithms based on Haar and Modified Haar techniques in attaining an efficient compression ratio (C.R, achieving higher peak signal to noise ratio (PSNR, and the resulting images are of much smoother as compared to standard JPEG especially for high C.R. A comparison between standard JPEG, Haar, and Modified Haar techniques is done finally which approves the highest capability of Modified Haar between others.

  19. Subband directional vector quantization in radiological image compression

    Science.gov (United States)

    Akrout, Nabil M.; Diab, Chaouki; Prost, Remy; Goutte, Robert; Amiel, Michel

    1992-05-01

    The aim of this paper is to propose a new scheme for image compression. The method is very efficient for images which have directional edges such as the tree-like structure of the coronary vessels in digital angiograms. This method involves two steps. First, the original image is decomposed at different resolution levels using a pyramidal subband decomposition scheme. For decomposition/reconstruction of the image, free of aliasing and boundary errors, we use an ideal band-pass filter bank implemented in the Discrete Cosine Transform domain (DCT). Second, the high-frequency subbands are vector quantized using a multiresolution codebook with vertical and horizontal codewords which take into account the edge orientation of each subband. The proposed method reduces the blocking effect encountered at low bit rates in conventional vector quantization.

  20. Edge-Based Image Compression with Homogeneous Diffusion

    Science.gov (United States)

    Mainberger, Markus; Weickert, Joachim

    It is well-known that edges contain semantically important image information. In this paper we present a lossy compression method for cartoon-like images that exploits information at image edges. These edges are extracted with the Marr-Hildreth operator followed by hysteresis thresholding. Their locations are stored in a lossless way using JBIG. Moreover, we encode the grey or colour values at both sides of each edge by applying quantisation, subsampling and PAQ coding. In the decoding step, information outside these encoded data is recovered by solving the Laplace equation, i.e. we inpaint with the steady state of a homogeneous diffusion process. Our experiments show that the suggested method outperforms the widely-used JPEG standard and can even beat the advanced JPEG2000 standard for cartoon-like images.

  1. COMPRESSING BIOMEDICAL IMAGE BY USING INTEGER WAVELET TRANSFORM AND PREDICTIVE ENCODER

    OpenAIRE

    Anushree Srivastava*, Narendra Kumar Chaurasia

    2016-01-01

    Image compression has become an important process in today’s world of information exchange. It helps in effective utilization of high speed network resources. Medical image compression has an important role in medical field because they are used for future reference of patients. Medical data is compressed in such a way so that the diagnostics capabilities are not compromised or no medical information is lost. Medical imaging poses the great challenge of having compression algorithms that redu...

  2. Development of a compressive sampling hyperspectral imager prototype

    Science.gov (United States)

    Barducci, Alessandro; Guzzi, Donatella; Lastri, Cinzia; Nardino, Vanni; Marcoionni, Paolo; Pippi, Ivan

    2013-10-01

    Compressive sensing (CS) is a new technology that investigates the chance to sample signals at a lower rate than the traditional sampling theory. The main advantage of CS is that compression takes place during the sampling phase, making possible significant savings in terms of the ADC, data storage memory, down-link bandwidth, and electrical power absorption. The CS technology could have primary importance for spaceborne missions and technology, paving the way to noteworthy reductions of payload mass, volume, and cost. On the contrary, the main CS disadvantage is made by the intensive off-line data processing necessary to obtain the desired source estimation. In this paper we summarize the CS architecture and its possible implementations for Earth observation, giving evidence of possible bottlenecks hindering this technology. CS necessarily employs a multiplexing scheme, which should produce some SNR disadvantage. Moreover, this approach would necessitate optical light modulators and 2-dim detector arrays of high frame rate. This paper describes the development of a sensor prototype at laboratory level that will be utilized for the experimental assessment of CS performance and the related reconstruction errors. The experimental test-bed adopts a push-broom imaging spectrometer, a liquid crystal plate, a standard CCD camera and a Silicon PhotoMultiplier (SiPM) matrix. The prototype is being developed within the framework of the ESA ITI-B Project titled "Hyperspectral Passive Satellite Imaging via Compressive Sensing".

  3. MO-B-BRC-00: Prostate HDR Treatment Planning - Considering Different Imaging Modalities

    International Nuclear Information System (INIS)

    2016-01-01

    Brachytherapy has proven to be an effective treatment option for prostate cancer. Initially, prostate brachytherapy was delivered through permanently implanted low dose rate (LDR) radioactive sources; however, high dose rate (HDR) temporary brachytherapy for prostate cancer is gaining popularity. Needle insertion during prostate brachytherapy is most commonly performed under ultrasound (U/S) guidance; however, treatment planning may be performed utilizing several imaging modalities either in an intra- or post-operative setting. During intra-operative prostate HDR, the needles are imaged during implantation, and planning may be performed in real time. At present, the most common imaging modality utilized for intra-operative prostate HDR is U/S. Alternatively, in the post-operative setting, following needle implantation, patients may be simulated with computed tomography (CT) or magnetic resonance imaging (MRI). Each imaging modality and workflow provides its share of benefits and limitations. Prostate HDR has been adopted in a number of cancer centers across the nation. In this educational session, we will explore the role of U/S, CT, and MRI in HDR prostate brachytherapy. Example workflows and operational details will be shared, and we will discuss how to establish a prostate HDR program in a clinical setting. Learning Objectives: Review prostate HDR techniques based on the imaging modality Discuss the challenges and pitfalls introduced by the three imagebased options for prostate HDR brachytherapy Review the QA process and learn about the development of clinical workflows for these imaging options at different institutions

  4. MO-B-BRC-00: Prostate HDR Treatment Planning - Considering Different Imaging Modalities

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2016-06-15

    Brachytherapy has proven to be an effective treatment option for prostate cancer. Initially, prostate brachytherapy was delivered through permanently implanted low dose rate (LDR) radioactive sources; however, high dose rate (HDR) temporary brachytherapy for prostate cancer is gaining popularity. Needle insertion during prostate brachytherapy is most commonly performed under ultrasound (U/S) guidance; however, treatment planning may be performed utilizing several imaging modalities either in an intra- or post-operative setting. During intra-operative prostate HDR, the needles are imaged during implantation, and planning may be performed in real time. At present, the most common imaging modality utilized for intra-operative prostate HDR is U/S. Alternatively, in the post-operative setting, following needle implantation, patients may be simulated with computed tomography (CT) or magnetic resonance imaging (MRI). Each imaging modality and workflow provides its share of benefits and limitations. Prostate HDR has been adopted in a number of cancer centers across the nation. In this educational session, we will explore the role of U/S, CT, and MRI in HDR prostate brachytherapy. Example workflows and operational details will be shared, and we will discuss how to establish a prostate HDR program in a clinical setting. Learning Objectives: Review prostate HDR techniques based on the imaging modality Discuss the challenges and pitfalls introduced by the three imagebased options for prostate HDR brachytherapy Review the QA process and learn about the development of clinical workflows for these imaging options at different institutions.

  5. Value of imaging modalities in sinus tarsi syndrome

    International Nuclear Information System (INIS)

    Young, J.W.R.; Resnick, C.S.; Kenzora, J.E.

    1989-01-01

    Sinus tarsi syndrome consists of ankle pain, giving way of the ankle, and tenderness over the sinus tarsi after acute ankle injury (usually inversion). Plan radiographic evaluation is unrewarding. This paper reports on stress CT scanning performed in 25 patients with sinus tarsi syndrome; 18 of these patients also underwent MR imaging; and all patients had routine radiographs. No consistent significant abnormalities were seen on CT. Ligamentous injury of the calcaneofibular or talocalcaneal ligament was suggested on MR images in six cases. Therefore, CT was not helpful in evaluating sinus tarsi syndrome, and the MR findings were present in only one-third of cases, suggesting either that MR imaging is not at present sufficiently accurate to detect all abnormalities or ligamentous injury is not the underlying cause for sinus tarsi syndrome

  6. Development of in vivo imaging modalities for experimental oncology

    International Nuclear Information System (INIS)

    Pesnel, S.

    2010-01-01

    Small animal imaging is more and more used in pharmacology to identify and to characterize the activities of new antitumor agents. The first part of my work consisted in the development of new tools to improve the quantitation in bioluminescence. A method, based on spectral characteristics of emitted photons, has been established to correct tissue absorption. The second, using methods of image restoration had for objective to correct tissue scattering to increase the resolution. In a second part, I developed in vivo models of bioluminescent tumors (intracranial glioblastoma, a large cell anaplastic lymphoma and a metastatic neuroblastoma) using the imaging methods described previously. These studies allowed the characterization of the activity of a new antitumor agent. The aim of the last part was to develop imaging probes. The first, a monoclonal antibody antiCD45 labeled with a fluoro chrome allowed the detection of human leukemic cells implanted in the mice using fluorescence imaging. The second was developed to predict the uptake of a antitumor agent, a spermine-podophyllotoxin conjugate, in tumor cells via the polyamine transport system. The synthesized probe is a spermine conjugated to a HYNIC group to bind a radioisotope: the Technetium-99m and to realize a scintigraphic examination. The results showed the feasibility of a preclinical use of this probe. So, at this end of this thesis, the developed methods of bioluminescent signal processing are available to improve the use of optical imaging in pharmacology. Of course, supplementary studies are necessary to define precisely in which context these corrections will be the most appropriate. (author)

  7. Robotic 3D scanner as an alternative to standard modalities of medical imaging.

    Science.gov (United States)

    Chromy, Adam; Zalud, Ludek

    2014-01-01

    There are special medical cases, where standard medical imaging modalities are able to offer sufficient results, but not in the optimal way. It means, that desired results are produced with unnecessarily high expenses, with redundant informations or with needless demands on patient. This paper deals with one special case, where information useful for examination is the body surface only, inner sight into the body is needless. New specialized medical imaging device is developed for this situation. In the Introduction section, analysis of presently used medical imaging modalities is presented, which declares, that no available imaging device is best fitting for mentioned purposes. In the next section, development of the new specialized medical imaging device is presented, and its principles and functions are described. Then, the parameters of new device are compared with present ones. It brings significant advantages comparing to present imaging systems.

  8. Dual modality CT/PET imaging in lung cancer staging

    International Nuclear Information System (INIS)

    Diaz, Gabriel A.

    2005-01-01

    Purpose: To compare the diagnostic capability of PET-HCT image fusion and helical computed tomography (HCT) for nodal and distant metastases detection in patients with lung cancer. Material and methods: Between February, 2003 and March, 2004 sixty-six consecutive lung cancer patients (45 men and 21 women, mean ages: 63 years old, range: 38 to 96 years old) who underwent HCT and PET-HCT fusion imaging were evaluated retrospectively. All patients had histological confirmation of lung cancer and a definitive diagnosis established on the basis of pathology results and/or clinical follow-up. Results: For global nodal staging (hilar and mediastinal) HCT showed a sensitivity, specificity, positive predictive value and negative predictive value of 72%, 47%, 62% and 58% respectively, versus 94%, 77%, 83% and 92% corresponding to PET-HCT examination. For assessment of advanced nodal stage (N3) PET-HCT showed values of 92%, 100%, 100% and 98% respectively. For detection of distant metastasis, HCT alone had values of 67%, 93%, 84% and 83% respectively versus 100%, 98%, 96% and 100% for the PET-HCT fusion imaging. In 20 (30%) patients under-staged or over-staged on the basis of HCT results, PET-HCT allowed accurate staging. Conclusions: PET-HCT fusion imaging was more effective than HCT alone for nodal and distant metastasis detection and oncology staging. (author)

  9. Accuracy of different imaging modalities prior to biventricular repair ...

    African Journals Online (AJOL)

    Arun Kumar Agnihotri

    catheterization with invasive angiocardiography is indicated when the PA ... arterial and venous imaging.3,4. The major ... history of aorto-pulmonary shunt awaiting bi-ventricular ..... regarding the central and peripheral PAs, APCs as well as in ...

  10. Percutaneous Ultrasonography as Imaging Modality and Sampling Guide for Pulmonologists

    NARCIS (Netherlands)

    Stigt, Jos A.; Groen, Harry J. M.

    2014-01-01

    Ultrasound (US) imaging is gradually progressing into common practice in contemporary pulmonology. Its main applications are to determine the presence and amount of pleural effusions and to guide subsequent treatment interventions. Guidelines recommend the use of US for these indications. Training

  11. Multi-modal image registration: matching MRI with histology

    NARCIS (Netherlands)

    Alić, L.; Haeck, J.C.; Klein, S.; Bol, K.; Tiel, S.T. van; Wielopolski, P.A.; Bijster, M.; Niessen, W.J.; Bernsen, M.; Veenland, J.F.; Jong, M. de

    2010-01-01

    Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co

  12. Comparisons of three alternative breast modalities in a common phantom imaging experiment

    International Nuclear Information System (INIS)

    Li Dun; Meaney, Paul M.; Tosteson, Tor D.; Jiang Shudong; Kerner, Todd E.; McBride, Troy O.; Pogue, Brian W.; Hartov, Alexander; Paulsen, Keith D.

    2003-01-01

    Four model-based imaging systems are currently being developed for breast cancer detection at Dartmouth College. A potential advantage of multimodality imaging is the prospect of combining information collected from each system to provide a more complete diagnostic tool that covers the full range of the patient and pathology spectra. In this paper it is shown through common phantom experiments on three of these imaging systems that it was possible to correlate different types of image information to potentially improve the reliability of tumor detection. Imaging experiments were conducted with common phantoms which mimic both dielectric and optical properties of the human breast. Cross modality comparison was investigated through a statistical study based on the repeated data sets of reconstructed parameters for each modality. The system standard error between all methods was generally less than 10% and the correlation coefficient across modalities ranged from 0.68 to 0.91. Future work includes the minimization of bias (artifacts) on the periphery of electrical impedance spectroscopy images to improve cross modality correlation and implementation of the multimodality diagnosis for breast cancer detection

  13. Accuracy and reproducibility of tumor positioning during prolonged and multi-modality animal imaging studies

    International Nuclear Information System (INIS)

    Zhang Mutian; Huang Minming; Le, Carl; Zanzonico, Pat B; Ling, C Clifton; Koutcher, Jason A; Humm, John L; Claus, Filip; Kolbert, Katherine S; Martin, Kyle

    2008-01-01

    Dedicated small-animal imaging devices, e.g. positron emission tomography (PET), computed tomography (CT) and magnetic resonance imaging (MRI) scanners, are being increasingly used for translational molecular imaging studies. The objective of this work was to determine the positional accuracy and precision with which tumors in situ can be reliably and reproducibly imaged on dedicated small-animal imaging equipment. We designed, fabricated and tested a custom rodent cradle with a stereotactic template to facilitate registration among image sets. To quantify tumor motion during our small-animal imaging protocols, 'gold standard' multi-modality point markers were inserted into tumor masses on the hind limbs of rats. Three types of imaging examination were then performed with the animals continuously anesthetized and immobilized: (i) consecutive microPET and MR images of tumor xenografts in which the animals remained in the same scanner for 2 h duration, (ii) multi-modality imaging studies in which the animals were transported between distant imaging devices and (iii) serial microPET scans in which the animals were repositioned in the same scanner for subsequent images. Our results showed that the animal tumor moved by less than 0.2-0.3 mm over a continuous 2 h microPET or MR imaging session. The process of transporting the animal between instruments introduced additional errors of ∼0.2 mm. In serial animal imaging studies, the positioning reproducibility within ∼0.8 mm could be obtained.

  14. Establishment study of the in vivo imaging analysis with small animal imaging modalities for bio-durg development

    International Nuclear Information System (INIS)

    Jang, Beomsu; Park, Sanghyeon; Choi, Dae Seong; Park, Jeonghoon; Jung, Uhee; Lee, Yun Jong

    2012-01-01

    In this study, we established the image modalities (micro-PET, SPECT/CT) using the experimental animal (mouse) for the development of imaging assessment method for the bio-durg and extramural collaboration proposal. We examined the micro-SPECT/CT, PET imaging study using the Siemens Inveon micro-multimodality system (SPECT/CT) and imaging study using the Siemens Inveon micro-multimodality system (SPECT/CT) and micro-PET with 99m Tc tricarbonyl bifunctional chelators and 18 F-clotrimazole derivative. SPECT imaging studies were performed with 99m Tc tricarbonyl BFCs. PET imaging study was performed with 18 F-clotrimazole derivatives. We performed the PET image study of 18 F-clotrimazole derivatives using U87MG tumor bearing mice. Also we tested the intramural and extramural collaboration using small animal imaging modalities and prepared the draft of extramural R and D operation manual for small animal imaging modalities and the experimental animal imaging facility. These research results can be utilized as a basic image study protocols and data for the image assessment of drugs including biological drug

  15. Accelerated dynamic EPR imaging using fast acquisition and compressive recovery.

    Science.gov (United States)

    Ahmad, Rizwan; Samouilov, Alexandre; Zweier, Jay L

    2016-12-01

    Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Efficient burst image compression using H.265/HEVC

    Science.gov (United States)

    Roodaki-Lavasani, Hoda; Lainema, Jani

    2014-02-01

    New imaging use cases are emerging as more powerful camera hardware is entering consumer markets. One family of such use cases is based on capturing multiple pictures instead of just one when taking a photograph. That kind of a camera operation allows e.g. selecting the most successful shot from a sequence of images, showing what happened right before or after the shot was taken or combining the shots by computational means to improve either visible characteristics of the picture (such as dynamic range or focus) or the artistic aspects of the photo (e.g. by superimposing pictures on top of each other). Considering that photographic images are typically of high resolution and quality and the fact that these kind of image bursts can consist of at least tens of individual pictures, an efficient compression algorithm is desired. However, traditional video coding approaches fail to provide the random access properties these use cases require to achieve near-instantaneous access to the pictures in the coded sequence. That feature is critical to allow users to browse the pictures in an arbitrary order or imaging algorithms to extract desired pictures from the sequence quickly. This paper proposes coding structures that provide such random access properties while achieving coding efficiency superior to existing image coders. The results indicate that using HEVC video codec with a single reference picture fixed for the whole sequence can achieve nearly as good compression as traditional IPPP coding structures. It is also shown that the selection of the reference frame can further improve the coding efficiency.

  17. On use of image quality metrics for perceptual blur modeling: image/video compression case

    Science.gov (United States)

    Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

    2018-02-01

    Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

  18. Real-time Image Generation for Compressive Light Field Displays

    International Nuclear Information System (INIS)

    Wetzstein, G; Lanman, D; Hirsch, M; Raskar, R

    2013-01-01

    With the invention of integral imaging and parallax barriers in the beginning of the 20th century, glasses-free 3D displays have become feasible. Only today—more than a century later—glasses-free 3D displays are finally emerging in the consumer market. The technologies being employed in current-generation devices, however, are fundamentally the same as what was invented 100 years ago. With rapid advances in optical fabrication, digital processing power, and computational perception, a new generation of display technology is emerging: compressive displays exploring the co-design of optical elements and computational processing while taking particular characteristics of the human visual system into account. In this paper, we discuss real-time implementation strategies for emerging compressive light field displays. We consider displays composed of multiple stacked layers of light-attenuating or polarization-rotating layers, such as LCDs. The involved image generation requires iterative tomographic image synthesis. We demonstrate that, for the case of light field display, computed tomographic light field synthesis maps well to operations included in the standard graphics pipeline, facilitating efficient GPU-based implementations with real-time framerates.

  19. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  20. Comparison of JPEG and wavelet compression on intraoral digital radiographic images

    International Nuclear Information System (INIS)

    Kim, Eun Kyung

    2004-01-01

    To determine the proper image compression method and ratio without image quality degradation in intraoral digital radiographic images, comparing the discrete cosine transform (DCT)-based JPEG with the wavelet-based JPEG 2000 algorithm. Thirty extracted sound teeth and thirty extracted teeth with occlusal caries were used for this study. Twenty plaster blocks were made with three teeth each. They were radiographically exposed using CDR sensors (Schick Inc., Long Island, USA). Digital images were compressed to JPEG format, using Adobe Photoshop v. 7.0 and JPEG 2000 format using Jasper program with compression ratios of 5 : 1, 9 : 1, 14 : 1, 28 : 1 each. To evaluate the lesion detectability, receiver operating characteristic (ROC) analysis was performed by the three oral and maxillofacial radiologists. To evaluate the image quality, all the compressed images were assessed subjectively using 5 grades, in comparison to the original uncompressed images. Compressed images up to compression ratio of 14: 1 in JPEG and 28 : 1 in JPEG 2000 showed nearly the same the lesion detectability as the original images. In the subjective assessment of image quality, images up to compression ratio of 9 : 1 in JPEG and 14 : 1 in JPEG 2000 showed minute mean paired differences from the original images. The results showed that the clinically acceptable compression ratios were up to 9 : 1 for JPEG and 14 : 1 for JPEG 2000. The wavelet-based JPEG 2000 is a better compression method, comparing to DCT-based JPEG for intraoral digital radiographic images.

  1. Designing sparse sensing matrix for compressive sensing to reconstruct high resolution medical images

    Directory of Open Access Journals (Sweden)

    Vibha Tiwari

    2015-12-01

    Full Text Available Compressive sensing theory enables faithful reconstruction of signals, sparse in domain $ \\Psi $, at sampling rate lesser than Nyquist criterion, while using sampling or sensing matrix $ \\Phi $ which satisfies restricted isometric property. The role played by sensing matrix $ \\Phi $ and sparsity matrix $ \\Psi $ is vital in faithful reconstruction. If the sensing matrix is dense then it takes large storage space and leads to high computational cost. In this paper, effort is made to design sparse sensing matrix with least incurred computational cost while maintaining quality of reconstructed image. The design approach followed is based on sparse block circulant matrix (SBCM with few modifications. The other used sparse sensing matrix consists of 15 ones in each column. The medical images used are acquired from US, MRI and CT modalities. The image quality measurement parameters are used to compare the performance of reconstructed medical images using various sensing matrices. It is observed that, since Gram matrix of dictionary matrix ($ \\Phi \\Psi \\mathrm{} $ is closed to identity matrix in case of proposed modified SBCM, therefore, it helps to reconstruct the medical images of very good quality.

  2. Joint Group Sparse PCA for Compressed Hyperspectral Imaging.

    Science.gov (United States)

    Khan, Zohaib; Shafait, Faisal; Mian, Ajmal

    2015-12-01

    A sparse principal component analysis (PCA) seeks a sparse linear combination of input features (variables), so that the derived features still explain most of the variations in the data. A group sparse PCA introduces structural constraints on the features in seeking such a linear combination. Collectively, the derived principal components may still require measuring all the input features. We present a joint group sparse PCA (JGSPCA) algorithm, which forces the basic coefficients corresponding to a group of features to be jointly sparse. Joint sparsity ensures that the complete basis involves only a sparse set of input features, whereas the group sparsity ensures that the structural integrity of the features is maximally preserved. We evaluate the JGSPCA algorithm on the problems of compressed hyperspectral imaging and face recognition. Compressed sensing results show that the proposed method consistently outperforms sparse PCA and group sparse PCA in reconstructing the hyperspectral scenes of natural and man-made objects. The efficacy of the proposed compressed sensing method is further demonstrated in band selection for face recognition.

  3. ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

    Science.gov (United States)

    Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

    2018-02-01

    Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

  4. Evaluation of compression ratio using JPEG 2000 on diagnostic images in dentistry

    International Nuclear Information System (INIS)

    Jung, Gi Hun; Han, Won Jeong; Yoo, Dong Soo; Kim, Eun Kyung; Choi, Soon Chul

    2005-01-01

    To find out the proper compression ratios without degrading image quality and affecting lesion detectability on diagnostic images used in dentistry compressed with JPEG 2000 algorithm. Sixty Digora peri apical images, sixty panoramic computed radiographic (CR) images, sixty computed tomography (CT) images, and sixty magnetic resonance (MR) images were compressed into JPEG 2000 with ratios of 10 levels from 5:1 to 50:1. To evaluate the lesion detectability, the images were graded with 5 levels (1 : definitely absent ; 2 : probably absent ; 3 : equivocal ; 4 : probably present ; 5 : definitely present), and then receiver operating characteristic analysis was performed using the original image as a gold standard. Also to evaluate subjectively the image quality, the images were graded with 5 levels (1 : definitely unacceptable ; 2 : probably unacceptable ; 3 : equivocal ; 4 : probably acceptable ; 5 : definitely acceptable), and then paired t-test was performed. In Digora, CR panoramic and CT images, compressed images up to ratios of 15:1 showed nearly the same lesion detectability as original images, and in MR images, compressed images did up to ratios of 25:1. In Digora and CR panoramic images, compressed images up to ratios of 5:1 showed little difference between the original and reconstructed images in subjective assessment of image quality. In CT images, compressed images did up to ratios of 10:1 and in MR images up to ratios of 15:1. We considered compression ratios up to 5:1 in Digora and CR panoramic images, up to 10:1 in CT images, up to 15:1 in MR images as clinically applicable compression ratios.

  5. Visual servoing in medical robotics: a survey. Part II: tomographic imaging modalities--techniques and applications.

    Science.gov (United States)

    Azizian, Mahdi; Najmaei, Nima; Khoshnam, Mahta; Patel, Rajni

    2015-03-01

    Intraoperative application of tomographic imaging techniques provides a means of visual servoing for objects beneath the surface of organs. The focus of this survey is on therapeutic and diagnostic medical applications where tomographic imaging is used in visual servoing. To this end, a comprehensive search of the electronic databases was completed for the period 2000-2013. Existing techniques and products are categorized and studied, based on the imaging modality and their medical applications. This part complements Part I of the survey, which covers visual servoing techniques using endoscopic imaging and direct vision. The main challenges in using visual servoing based on tomographic images have been identified. 'Supervised automation of medical robotics' is found to be a major trend in this field and ultrasound is the most commonly used tomographic modality for visual servoing. Copyright © 2014 John Wiley & Sons, Ltd.

  6. Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases

    KAUST Repository

    Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, Christian; Jourdain, P.; Magistretti, Pierre J.

    2016-01-01

    parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.

  7. Multi-Modality Imaging in the Evaluation and Treatment of Mitral Regurgitation.

    Science.gov (United States)

    Bouchard, Marc-André; Côté-Laroche, Claudia; Beaudoin, Jonathan

    2017-10-13

    Mitral regurgitation (MR) is frequent and associated with increased mortality and morbidity when severe. It may be caused by intrinsic valvular disease (primary MR) or ventricular deformation (secondary MR). Imaging has a critical role to document the severity, mechanism, and impact of MR on heart function as selected patients with MR may benefit from surgery whereas other will not. In patients planned for a surgical intervention, imaging is also important to select candidates for mitral valve (MV) repair over replacement and to predict surgical success. Although standard transthoracic echocardiography is the first-line modality to evaluate MR, newer imaging modalities like three-dimensional (3D) transesophageal echocardiography, stress echocardiography, cardiac magnetic resonance (CMR), and computed tomography (CT) are emerging and complementary tools for MR assessment. While some of these modalities can provide insight into MR severity, others will help to determine its mechanism. Understanding the advantages and limitations of each imaging modality is important to appreciate their respective role for MR assessment and help to resolve eventual discrepancies between different diagnostic methods. With the increasing use of transcatheter mitral procedures (repair or replacement) for high-surgical-risk patients, multimodality imaging has now become even more important to determine eligibility, preinterventional planning, and periprocedural guidance.

  8. COxSwAIN: Compressive Sensing for Advanced Imaging and Navigation

    Science.gov (United States)

    Kurwitz, Richard; Pulley, Marina; LaFerney, Nathan; Munoz, Carlos

    2015-01-01

    The COxSwAIN project focuses on building an image and video compression scheme that can be implemented in a small or low-power satellite. To do this, we used Compressive Sensing, where the compression is performed by matrix multiplications on the satellite and reconstructed on the ground. Our paper explains our methodology and demonstrates the results of the scheme, being able to achieve high quality image compression that is robust to noise and corruption.

  9. Multifunctional Magnetic and Upconverting Nanobeads as Dual Modal Imaging Tools.

    Science.gov (United States)

    Materia, Maria Elena; Pernia Leal, Manuel; Scotto, Marco; Balakrishnan, Preethi Bala; Kumar Avugadda, Sahitya; García-Martín, María L; Cohen, Bruce E; Chan, Emory M; Pellegrino, Teresa

    2017-11-15

    We report the fabrication of aqueous multimodal imaging nanocomposites based on superparamagnetic nanoparticles (MNPs) and two different sizes of photoluminescent upconverting nanoparticles (UCNPs). The controlled and simultaneous incorporation of both types of nanoparticles (NPs) was obtained by controlling the solvent composition and the addition rate of the destabilizing solvent. The magnetic properties of the MNPs remained unaltered after their encapsulation into the polymeric beads as shown by the T2 relaxivity measurements. The UCNPs maintain photoluminescent properties even when embedded with the MNPs into the polymer bead. Moreover, the light emitted by the magnetic and upconverting nanobeads (MUCNBs) under NIR excitation (λ exc = 980 nm) was clearly observed through different thicknesses of agarose gel or through a mouse skin layer. The comparison with magnetic and luminescent nanobeads based on red-emitting quantum dots (QDs) demonstrated that while the QD-based beads show significant autofluorescence background from the skin, the signal obtained by the MUCNBs allows a decrease in this background. In summary, these results indicate that MUCNBs are good magnetic and optical probes for in vivo multimodal imaging sensors.

  10. Multi-modal image registration: matching MRI with histology

    Science.gov (United States)

    Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

    2010-03-01

    Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

  11. New patient-controlled abdominal compression method in radiography: radiation dose and image quality.

    Science.gov (United States)

    Piippo-Huotari, Oili; Norrman, Eva; Anderzén-Carlsson, Agneta; Geijer, Håkan

    2018-05-01

    The radiation dose for patients can be reduced with many methods and one way is to use abdominal compression. In this study, the radiation dose and image quality for a new patient-controlled compression device were compared with conventional compression and compression in the prone position . To compare radiation dose and image quality of patient-controlled compression compared with conventional and prone compression in general radiography. An experimental design with quantitative approach. After obtaining the approval of the ethics committee, a consecutive sample of 48 patients was examined with the standard clinical urography protocol. The radiation doses were measured as dose-area product and analyzed with a paired t-test. The image quality was evaluated by visual grading analysis. Four radiologists evaluated each image individually by scoring nine criteria modified from the European quality criteria for diagnostic radiographic images. There was no significant difference in radiation dose or image quality between conventional and patient-controlled compression. Prone position resulted in both higher dose and inferior image quality. Patient-controlled compression gave similar dose levels as conventional compression and lower than prone compression. Image quality was similar with both patient-controlled and conventional compression and was judged to be better than in the prone position.

  12. Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

    Science.gov (United States)

    Elahi, Sana; kaleem, Muhammad; Omer, Hammad

    2018-01-01

    Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

  13. Role of magnetic resonance imaging (MRI), MR spectroscopy (MRS) and other imaging modalities in breast cancer

    International Nuclear Information System (INIS)

    Sharma, Uma; Virendra Kumar; Jagannathan, N.R.

    2004-01-01

    Breast cancer is the commonest cancer among women world over and the diagnosis continues to generate fear and turmoil in the life of patients and their families. This article describes the currently available techniques used for screening primary and recurrent breast cancers and the evaluation of therapeutic response of breast cancer with special emphasis on MRI and MRS techniques. MRI, a noninvasive technique, provides anatomic images in multiple planes enabling tissue characterization. Contrast enhanced MR studies have been found to be useful in the diagnosis of small tumors in dense breast benign diseases from malignant ones. In vivo magnetic resonance spectroscopy (MRS) is another useful technique for diagnosis and for assessing the biochemical status of normal and diseased tissues. Being noninvasive, MR techniques can be used repetitively for assessment of response of the tumor to various therapeutic regimens and for evaluating the efficacy of drugs at both the structural and molecular level. An overview of the various aspects of different imaging modalities used in breast cancer research including various in vivo MR methodologies with clinical examples is presented in this review. (author)

  14. Integration of vibro-acoustography imaging modality with the traditional mammography.

    Science.gov (United States)

    Hosseini, H Gholam; Alizad, A; Fatemi, M

    2007-01-01

    Vibro-acoustography (VA) is a new imaging modality that has been applied to both medical and industrial imaging. Integrating unique diagnostic information of VA with other medical imaging is one of our research interests. In this work, we establish correspondence between the VA images and traditional X-ray mammogram by adopting a flexible control-point selection technique for image registration. A modified second-order polynomial, which simply leads to a scale/rotation/translation invariant registration, was used. The results of registration were used to spatially transform the breast VA images to map with the X-ray mammography with a registration error of less than 1.65 mm. The fused image is defined as a linear integration of the VA and X-ray images. Moreover, a color-based fusion technique was employed to integrate the images for better visualization of structural information.

  15. Underwater Acoustic Matched Field Imaging Based on Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Huichen Yan

    2015-10-01

    Full Text Available Matched field processing (MFP is an effective method for underwater target imaging and localizing, but its performance is not guaranteed due to the nonuniqueness and instability problems caused by the underdetermined essence of MFP. By exploiting the sparsity of the targets in an imaging area, this paper proposes a compressive sensing MFP (CS-MFP model from wave propagation theory by using randomly deployed sensors. In addition, the model’s recovery performance is investigated by exploring the lower bounds of the coherence parameter of the CS dictionary. Furthermore, this paper analyzes the robustness of CS-MFP with respect to the displacement of the sensors. Subsequently, a coherence-excluding coherence optimized orthogonal matching pursuit (CCOOMP algorithm is proposed to overcome the high coherent dictionary problem in special cases. Finally, some numerical experiments are provided to demonstrate the effectiveness of the proposed CS-MFP method.

  16. Compressive Sampling for Non-Imaging Remote Classification

    Science.gov (United States)

    2013-10-22

    spectro -­‐polarization  imager,   a  compressive  coherence  imager  to  resolve  objects  through  turbulence...2    The  relay  lens  for   UV -­‐CASSI,  which  focuses  the  aperture  code  onto  the  monochrome  detector...below  in  Fig.  3,  with  a  silicon   UV  sensitive  detector  on  the  left,  and   a   UV

  17. Compression-Based Tools for Navigation with an Image Database

    Directory of Open Access Journals (Sweden)

    Giovanni Motta

    2012-01-01

    Full Text Available We present tools that can be used within a larger system referred to as a passive assistant. The system receives information from a mobile device, as well as information from an image database such as Google Street View, and employs image processing to provide useful information about a local urban environment to a user who is visually impaired. The first stage acquires and computes accurate location information, the second stage performs texture and color analysis of a scene, and the third stage provides specific object recognition and navigation information. These second and third stages rely on compression-based tools (dimensionality reduction, vector quantization, and coding that are enhanced by knowledge of (approximate location of objects.

  18. Medical image compression and its application to TDIS-FILE equipment

    International Nuclear Information System (INIS)

    Tsubura, Shin-ichi; Nishihara, Eitaro; Iwai, Shunsuke

    1990-01-01

    In order to compress medical images for filing and communication, we have developed a compression algorithm which compresses images with remarkable quality using a high-pass filtering method. Hardware for this compression algorithm was also developed and applied to TDIS (total digital imaging system)-FILE equipment. In the future, hardware based on this algorithm will be developed for various types of diagnostic equipment and PACS. This technique has the following characteristics: (1) significant reduction of artifacts; (2) acceptable quality for clinical evaluation at 15:1 to 20:1 compression ratio; and (3) high-speed processing and compact hardware. (author)

  19. Diagnostic imaging of compression neuropathy; Bildgebende Diagnostik von Nervenkompressionssyndromen

    Energy Technology Data Exchange (ETDEWEB)

    Weishaupt, D.; Andreisek, G. [Universitaetsspital, Institut fuer Diagnostische Radiologie, Zuerich (Switzerland)

    2007-03-15

    Compression-induced neuropathy of peripheral nerves can cause severe pain of the foot and ankle. Early diagnosis is important to institute prompt treatment and to minimize potential injury. Although clinical examination combined with electrophysiological studies remain the cornerstone of the diagnostic work-up, in certain cases, imaging may provide key information with regard to the exact anatomic location of the lesion or aid in narrowing the differential diagnosis. In other patients with peripheral neuropathies of the foot and ankle, imaging may establish the etiology of the condition and provide information crucial for management and/or surgical planning. MR imaging and ultrasound provide direct visualization of the nerve and surrounding abnormalities. Bony abnormalities contributing to nerve compression are best assessed by radiographs and CT. Knowledge of the anatomy, the etiology, typical clinical findings, and imaging features of peripheral neuropathies affecting the peripheral nerves of the foot and ankle will allow for a more confident diagnosis. (orig.) [German] Kompressionsbedingte Schaedigungen peripherer Nerven koennen die Ursache hartnaeckiger Schmerzen im Bereich des Sprunggelenks und Fusses sein. Eine fruehzeitige Diagnose ist entscheidend, um den Patienten der richtigen Therapie zuzufuehren und potenzielle Schaedigungen zu vermeiden oder zu verringern. Obschon die klinische Untersuchung und die elektrophysiologische Abklaerungen die wichtigsten Elemente der Diagnostik peripherer Nervenkompressionssyndrome sind, kann die Bildgebung entscheidend sein, wenn es darum geht, die Hoehe des Nervenschadens festzulegen oder die Differenzialdiagnose einzugrenzen. In gewissen Faellen kann durch Bildgebung sogar die Ursache der Nervenkompression gefunden werden. In anderen Faellen ist die Bildgebung wichtig bei der Therapieplanung, insbesondere dann, wenn die Laesion chirurgisch angegangen wird. Magnetresonanztomographie (MRT) und Sonographie ermoeglichen eine

  20. Learning-based compressed sensing for infrared image super resolution

    Science.gov (United States)

    Zhao, Yao; Sui, Xiubao; Chen, Qian; Wu, Shaochi

    2016-05-01

    This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.

  1. Congenital syphylitic hepatitis: a case report with multiple imaging modalities (syphilitic hepatitis)

    Energy Technology Data Exchange (ETDEWEB)

    Heyman, S; Rosenberg, H K; Mandell, G A; Golden, D A

    1983-11-14

    A case of syphilitic hepatitis is described with no evidence of mass effect on the ultrasonic and computerized tomographic study, but with discrete areas of decreased uptake on liver scan suggestive of space-occupying lesion. This is the second instance in the literature of the incongruence of the liver scan and the other imaging modalities in syphilitic hepatitis.

  2. Extended feature-fusion guidelines to improve image-based multi-modal biometrics

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-09-01

    Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

  3. Congenital syphylitic hepatitis: a case report with multiple imaging modalities (syphilitic hepatitis)

    International Nuclear Information System (INIS)

    Heyman, S.; Rosenberg, H.K.; Mandell, G.A.; Golden, D.A.

    1983-01-01

    A case of syphilitic hepatitis is described with no evidence of mass effect on the ultrasonic and computerized tomographic study, but discrete areas of decreased uptake on liver scan suggestive of space-occupying lesion. This is the second instance in the literature of the incongruence of the liver scan and the other imaging modalities in syphilitic hepatitis. (orig.)

  4. A highly sensitive x-ray imaging modality for hepatocellular carcinoma detection in vitro

    Science.gov (United States)

    Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; Wands, Jack R.; Rose-Petruck, Christoph

    2015-01-01

    Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called spatial frequency heterodyne imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. In this study we use numerical processing to produce x-ray scatter images of hepatocellular carcinoma labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and magnetic resonance imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. As x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities.

  5. Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding

    Directory of Open Access Journals (Sweden)

    Yongjian Nian

    2013-01-01

    Full Text Available A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC is proposed in this paper. The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression. Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information. Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression. Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate. Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.

  6. Diagnosis and Characterization of Patellofemoral Instability: Review of Available Imaging Modalities.

    Science.gov (United States)

    Haj-Mirzaian, Arya; Thawait, Gaurav K; Tanaka, Miho J; Demehri, Shadpour

    2017-06-01

    Patellofemoral instability (PI) is defined as single or multiple episodes of patellar dislocation. Imaging modalities are useful for characterization of patellar malalignment, maltracking, underlying morphologic abnormalities, and stabilizing soft-tissue injuries. Using these findings, orthopedic surgeons can decide when to operate, determine the best operation, and measure degree of correction postoperatively in PI patients. Also, these methods assist with PI diagnosis in some suspicious cases. Magnetic resonance imaging is the preferred method especially in the setting of acute dislocations. Multidetector computed tomography allows a more accurate assessment for malalignment such as patellar tilt and lateral subluxation and secondary osteoarthritis. Dynamic magnetic resonance imaging and 4-dimensional computed tomography have been introduced for better kinematic assessment of the patellofemoral maltracking during extension-flexion motions. In this review article, we will discuss the currently available evidence regarding both the conventional and the novel imaging modalities that can be used for diagnosis and characterization of PI.

  7. In Situ Imaging during Compression of Plastic Bonded Explosives for Damage Modeling

    Directory of Open Access Journals (Sweden)

    Virginia W. Manner

    2017-06-01

    Full Text Available The microstructure of plastic bonded explosives (PBXs is known to influence behavior during mechanical deformation, but characterizing the microstructure can be challenging. For example, the explosive crystals and binder in formulations such as PBX 9501 do not have sufficient X-ray contrast to obtain three-dimensional data by in situ, absorption contrast imaging. To address this difficulty, we have formulated a series of PBXs using octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX crystals and low-density binder systems. The binders were hydroxyl-terminated polybutadiene (HTPB or glycidyl azide polymer (GAP cured with a commercial blend of acrylic monomers/oligomers. The binder density is approximately half of the HMX, allowing for excellent contrast using in situ X-ray computed tomography (CT imaging. The samples were imaged during unaxial compression using micro-scale CT in an interrupted in situ modality. The rigidity of the binder was observed to significantly influence fracture, crystal-binder delamination, and flow. Additionally, 2D slices from the segmented 3D images were meshed for finite element simulation of the mesoscale response. At low stiffness, the binder and crystal do not delaminate and the crystals move with the material flow; at high stiffness, marked delamination is noted between the crystals and the binder, leading to very different mechanical properties. Initial model results exhibit qualitatively similar delamination.

  8. Single exposure optically compressed imaging and visualization using random aperture coding

    Energy Technology Data Exchange (ETDEWEB)

    Stern, A [Electro Optical Unit, Ben Gurion University of the Negev, Beer-Sheva 84105 (Israel); Rivenson, Yair [Department of Electrical and Computer Engineering, Ben Gurion University of the Negev, Beer-Sheva 84105 (Israel); Javidi, Bahrain [Department of Electrical and Computer Engineering, University of Connecticut, Storrs, Connecticut 06269-1157 (United States)], E-mail: stern@bgu.ac.il

    2008-11-01

    The common approach in digital imaging follows the sample-then-compress framework. According to this approach, in the first step as many pixels as possible are captured and in the second step the captured image is compressed by digital means. The recently introduced theory of compressed sensing provides the mathematical foundation necessary to combine these two steps in a single one, that is, to compress the information optically before it is recorded. In this paper we overview and extend an optical implementation of compressed sensing theory that we have recently proposed. With this new imaging approach the compression is accomplished inherently in the optical acquisition step. The primary feature of this imaging approach is a randomly encoded aperture realized by means of a random phase screen. The randomly encoded aperture implements random projection of the object field in the image plane. Using a single exposure, a randomly encoded image is captured which can be decoded by proper decoding algorithm.

  9. Image Quality Assessment for Different Wavelet Compression Techniques in a Visual Communication Framework

    Directory of Open Access Journals (Sweden)

    Nuha A. S. Alwan

    2013-01-01

    Full Text Available Images with subband coding and threshold wavelet compression are transmitted over a Rayleigh communication channel with additive white Gaussian noise (AWGN, after quantization and 16-QAM modulation. A comparison is made between these two types of compression using both mean square error (MSE and structural similarity (SSIM image quality assessment (IQA criteria applied to the reconstructed image at the receiver. The two methods yielded comparable SSIM but different MSE measures. In this work, we justify our results which support previous findings in the literature that the MSE between two images is not indicative of structural similarity or the visibility of errors. It is found that it is difficult to reduce the pointwise errors in subband-compressed images (higher MSE. However, the compressed images provide comparable SSIM or perceived quality for both types of compression provided that the retained energy after compression is the same.

  10. Acquisition of STEM Images by Adaptive Compressive Sensing

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Weiyi; Feng, Qianli; Srinivasan, Ramprakash; Stevens, Andrew; Browning, Nigel D.

    2017-07-01

    Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5] are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However

  11. Statistical Analysis of Compression Methods for Storing Binary Image for Low-Memory Systems

    Directory of Open Access Journals (Sweden)

    Roman Slaby

    2013-01-01

    Full Text Available The paper is focused on the statistical comparison of the selected compression methods which are used for compression of the binary images. The aim is to asses, which of presented compression method for low-memory system requires less number of bytes of memory. For assessment of the success rates of the input image to binary image the correlation functions are used. Correlation function is one of the methods of OCR algorithm used for the digitization of printed symbols. Using of compression methods is necessary for systems based on low-power micro-controllers. The data stream saving is very important for such systems with limited memory as well as the time required for decoding the compressed data. The success rate of the selected compression algorithms is evaluated using the basic characteristics of the exploratory analysis. The searched samples represent the amount of bytes needed to compress the test images, representing alphanumeric characters.

  12. Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images

    DEFF Research Database (Denmark)

    Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas

    2014-01-01

    Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also pr...... as a convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research....

  13. Image-Data Compression Using Edge-Optimizing Algorithm for WFA Inference.

    Science.gov (United States)

    Culik, Karel II; Kari, Jarkko

    1994-01-01

    Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

  14. Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

    OpenAIRE

    Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

    2012-01-01

    An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with vari...

  15. Accurate reconstruction of hyperspectral images from compressive sensing measurements

    Science.gov (United States)

    Greer, John B.; Flake, J. C.

    2013-05-01

    The emerging field of Compressive Sensing (CS) provides a new way to capture data by shifting the heaviest burden of data collection from the sensor to the computer on the user-end. This new means of sensing requires fewer measurements for a given amount of information than traditional sensors. We investigate the efficacy of CS for capturing HyperSpectral Imagery (HSI) remotely. We also introduce a new family of algorithms for constructing HSI from CS measurements with Split Bregman Iteration [Goldstein and Osher,2009]. These algorithms combine spatial Total Variation (TV) with smoothing in the spectral dimension. We examine models for three different CS sensors: the Coded Aperture Snapshot Spectral Imager-Single Disperser (CASSI-SD) [Wagadarikar et al.,2008] and Dual Disperser (CASSI-DD) [Gehm et al.,2007] cameras, and a hypothetical random sensing model closer to CS theory, but not necessarily implementable with existing technology. We simulate the capture of remotely sensed images by applying the sensor forward models to well-known HSI scenes - an AVIRIS image of Cuprite, Nevada and the HYMAP Urban image. To measure accuracy of the CS models, we compare the scenes constructed with our new algorithm to the original AVIRIS and HYMAP cubes. The results demonstrate the possibility of accurately sensing HSI remotely with significantly fewer measurements than standard hyperspectral cameras.

  16. Interpolation decoding method with variable parameters for fractal image compression

    International Nuclear Information System (INIS)

    He Chuanjiang; Li Gaoping; Shen Xiaona

    2007-01-01

    The interpolation fractal decoding method, which is introduced by [He C, Yang SX, Huang X. Progressive decoding method for fractal image compression. IEE Proc Vis Image Signal Process 2004;3:207-13], involves generating progressively the decoded image by means of an interpolation iterative procedure with a constant parameter. It is well-known that the majority of image details are added at the first steps of iterations in the conventional fractal decoding; hence the constant parameter for the interpolation decoding method must be set as a smaller value in order to achieve a better progressive decoding. However, it needs to take an extremely large number of iterations to converge. It is thus reasonable for some applications to slow down the iterative process at the first stages of decoding and then to accelerate it afterwards (e.g., at some iteration as we need). To achieve the goal, this paper proposed an interpolation decoding scheme with variable (iteration-dependent) parameters and proved the convergence of the decoding process mathematically. Experimental results demonstrate that the proposed scheme has really achieved the above-mentioned goal

  17. Block Compressed Sensing of Images Using Adaptive Granular Reconstruction

    Directory of Open Access Journals (Sweden)

    Ran Li

    2016-01-01

    Full Text Available In the framework of block Compressed Sensing (CS, the reconstruction algorithm based on the Smoothed Projected Landweber (SPL iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.

  18. Continuous monitoring of arthritis in animal models using optical imaging modalities

    Science.gov (United States)

    Son, Taeyoon; Yoon, Hyung-Ju; Lee, Saseong; Jang, Won Seuk; Jung, Byungjo; Kim, Wan-Uk

    2014-10-01

    Given the several difficulties associated with histology, including difficulty in continuous monitoring, this study aimed to investigate the feasibility of optical imaging modalities-cross-polarization color (CPC) imaging, erythema index (EI) imaging, and laser speckle contrast (LSC) imaging-for continuous evaluation and monitoring of arthritis in animal models. C57BL/6 mice, used for the evaluation of arthritis, were divided into three groups: arthritic mice group (AMG), positive control mice group (PCMG), and negative control mice group (NCMG). Complete Freund's adjuvant, mineral oil, and saline were injected into the footpad for AMG, PCMG, and NCMG, respectively. LSC and CPC images were acquired from 0 through 144 h after injection for all groups. EI images were calculated from CPC images. Variations in feet area, EI, and speckle index for each mice group over time were calculated for quantitative evaluation of arthritis. Histological examinations were performed, and the results were found to be consistent with those from optical imaging analysis. Thus, optical imaging modalities may be successfully applied for continuous evaluation and monitoring of arthritis in animal models.

  19. Visual tracking for multi-modality computer-assisted image guidance

    Science.gov (United States)

    Basafa, Ehsan; Foroughi, Pezhman; Hossbach, Martin; Bhanushali, Jasmine; Stolka, Philipp

    2017-03-01

    With optical cameras, many interventional navigation tasks previously relying on EM, optical, or mechanical guidance can be performed robustly, quickly, and conveniently. We developed a family of novel guidance systems based on wide-spectrum cameras and vision algorithms for real-time tracking of interventional instruments and multi-modality markers. These navigation systems support the localization of anatomical targets, support placement of imaging probe and instruments, and provide fusion imaging. The unique architecture - low-cost, miniature, in-hand stereo vision cameras fitted directly to imaging probes - allows for an intuitive workflow that fits a wide variety of specialties such as anesthesiology, interventional radiology, interventional oncology, emergency medicine, urology, and others, many of which see increasing pressure to utilize medical imaging and especially ultrasound, but have yet to develop the requisite skills for reliable success. We developed a modular system, consisting of hardware (the Optical Head containing the mini cameras) and software (components for visual instrument tracking with or without specialized visual features, fully automated marker segmentation from a variety of 3D imaging modalities, visual observation of meshes of widely separated markers, instant automatic registration, and target tracking and guidance on real-time multi-modality fusion views). From these components, we implemented a family of distinct clinical and pre-clinical systems (for combinations of ultrasound, CT, CBCT, and MRI), most of which have international regulatory clearance for clinical use. We present technical and clinical results on phantoms, ex- and in-vivo animals, and patients.

  20. Image quality and dose distributions of three linac-based imaging modalities

    Energy Technology Data Exchange (ETDEWEB)

    Dzierma, Yvonne; Ames, Evemarie; Nuesken, Frank; Palm, Jan; Licht, Norbert; Ruebe, Christian [Universitaetsklinikum des Saarlandes, Klinik fuer Strahlentherapie und Radioonkologie, Homburg/Saar (Germany)

    2015-04-01

    Linac-based patient imaging is possible with a variety of techniques using different photon energies. The purpose of this work is to compare three imaging systems operating at 6 MV, flattening free filter (FFF) 1 MV, and 121 kV. The dose distributions of all pretreatment set-up images (over 1,000) were retrospectively calculated on the planning computed tomography (CT) images for all patients with prostate and head-and-neck cancer treated at our institution in 2013. We analyzed the dose distribution and the dose to organs at risk. For head-and-neck cancer patients, the imaging dose from 6-MV cone beam CT (CBCT) reached maximum values at around 8 cGy. The 1-MV CBCT dose was about 63-79 % of the 6-MV CBCT dose for all organs at risk. Planar imaging reduced the imaging dose from CBCT to 30-40 % for both megavoltage modalities. The dose from the kilovoltage CBCT was 4-10 % of the 6-MV CBCT dose. For prostate cancer patients, the maximum dose from 6-MV CBCT reached 13-15 cGy, and was reduced to 66-73 % for 1 MV. Planar imaging reduces the MV CBCT dose to 10-20 %. The kV CBCT dose is 15-20 % of the 6-MV CBCT dose, slightly higher than the dose from MV axes. The dose distributions differ markedly in response to the different beam profiles and dose-depth characteristics. (orig.) [German] Linac-basierte Bildgebung zur Patientenlagerung ist mit einer Vielzahl von Techniken unterschiedlicher Photonenenergien moeglich. Ziel dieser Arbeit ist der Vergleich dreier Bildgebungssysteme mit 6 MV (Megavolt), FFF 1 MV, und 121 kV (Kilovolt). Fuer alle im Jahr 2013 an unserer Klinik behandelten Prostata- und HNO-Patienten wurden retrospektiv die Dosisverteilungen aller Verifikationsaufnahmen (ueber 1000 insgesamt) auf der Planungs-Computertomographie (CT) berechnet. Wir analysierten die Dosisverteilung und die Dosis an den Risikoorganen. Bei HNO-Patienten erreichte die Dosis von 6 MV ''Cone-beam''-CT (CBCT)Maximalwerte um 8 cGy. Mit 1 MV wird die Dosis auf 63

  1. Dual photon excitation microscopy and image threshold segmentation in live cell imaging during compression testing.

    Science.gov (United States)

    Moo, Eng Kuan; Abusara, Ziad; Abu Osman, Noor Azuan; Pingguan-Murphy, Belinda; Herzog, Walter

    2013-08-09

    Morphological studies of live connective tissue cells are imperative to helping understand cellular responses to mechanical stimuli. However, photobleaching is a constant problem to accurate and reliable live cell fluorescent imaging, and various image thresholding methods have been adopted to account for photobleaching effects. Previous studies showed that dual photon excitation (DPE) techniques are superior over conventional one photon excitation (OPE) confocal techniques in minimizing photobleaching. In this study, we investigated the effects of photobleaching resulting from OPE and DPE on morphology of in situ articular cartilage chondrocytes across repeat laser exposures. Additionally, we compared the effectiveness of three commonly-used image thresholding methods in accounting for photobleaching effects, with and without tissue loading through compression. In general, photobleaching leads to an apparent volume reduction for subsequent image scans. Performing seven consecutive scans of chondrocytes in unloaded cartilage, we found that the apparent cell volume loss caused by DPE microscopy is much smaller than that observed using OPE microscopy. Applying scan-specific image thresholds did not prevent the photobleaching-induced volume loss, and volume reductions were non-uniform over the seven repeat scans. During cartilage loading through compression, cell fluorescence increased and, depending on the thresholding method used, led to different volume changes. Therefore, different conclusions on cell volume changes may be drawn during tissue compression, depending on the image thresholding methods used. In conclusion, our findings confirm that photobleaching directly affects cell morphology measurements, and that DPE causes less photobleaching artifacts than OPE for uncompressed cells. When cells are compressed during tissue loading, a complicated interplay between photobleaching effects and compression-induced fluorescence increase may lead to interpretations in

  2. Automatic classification of early Parkinson's disease with multi-modal MR imaging.

    Directory of Open Access Journals (Sweden)

    Dan Long

    Full Text Available BACKGROUND: In recent years, neuroimaging has been increasingly used as an objective method for the diagnosis of Parkinson's disease (PD. Most previous studies were based on invasive imaging modalities or on a single modality which was not an ideal diagnostic tool. In this study, we developed a non-invasive technology intended for use in the diagnosis of early PD by integrating the advantages of various modals. MATERIALS AND METHODS: Nineteen early PD patients and twenty-seven normal volunteers participated in this study. For each subject, we collected resting-state functional magnetic resonance imaging (rsfMRI and structural images. For the rsfMRI images, we extracted the characteristics at three different levels: ALFF (amplitude of low-frequency fluctuations, ReHo (regional homogeneity and RFCS (regional functional connectivity strength. For the structural images, we extracted the volume characteristics from the gray matter (GM, the white matter (WM and the cerebrospinal fluid (CSF. A two-sample t-test was used for the feature selection, and then the remaining features were fused for classification. Finally a classifier for early PD patients and normal control subjects was identified from support vector machine training. The performance of the classifier was evaluated using the leave-one-out cross-validation method. RESULTS: Using the proposed methods to classify the data set, good results (accuracy  = 86.96%, sensitivity  = 78.95%, specificity  = 92.59% were obtained. CONCLUSIONS: This method demonstrates a promising diagnosis performance by the integration of information from a variety of imaging modalities, and it shows potential for improving the clinical diagnosis and treatment of PD.

  3. Magnetic resonance imaging in cervical spinal cord compression

    Directory of Open Access Journals (Sweden)

    Giovanni Giammona

    1993-09-01

    Full Text Available In patients with cervical spondylotic myelopathy MRI sometimes shows increased signal intensity zones on the T2-weighted images. It has been suggested that these findings carry prognostic significance. We studied 56 subjects with cervical spinal cord compression. Twelve patients showed an increased signal intensity (21.4% and a prevalence of narrowing of the AP-diameter (62% vs 24%. Furthemore, in this group, there was evidence of a longer mean duration of the symptoms and, in most of the patients, of more serious clinical conditions. The importance of these predisposing factors remains, however, to be clarified since they are also present in some patients without the increased signal intensity.

  4. Optimal context quantization in lossless compression of image data sequences

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Wu, X.; Andersen, Jakob Dahl

    2004-01-01

    In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due...... to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context C/sub t/=(X/sub t-t1/,X/sub t-t2/,...,X/sub t-tK/) of a source symbol X/sub t/ into one of a set of conditioning states. The optimality of context...... quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet...

  5. Intelligent fuzzy approach for fast fractal image compression

    Science.gov (United States)

    Nodehi, Ali; Sulong, Ghazali; Al-Rodhaan, Mznah; Al-Dhelaan, Abdullah; Rehman, Amjad; Saba, Tanzila

    2014-12-01

    Fractal image compression (FIC) is recognized as a NP-hard problem, and it suffers from a high number of mean square error (MSE) computations. In this paper, a two-phase algorithm was proposed to reduce the MSE computation of FIC. In the first phase, based on edge property, range and domains are arranged. In the second one, imperialist competitive algorithm (ICA) is used according to the classified blocks. For maintaining the quality of the retrieved image and accelerating algorithm operation, we divided the solutions into two groups: developed countries and undeveloped countries. Simulations were carried out to evaluate the performance of the developed approach. Promising results thus achieved exhibit performance better than genetic algorithm (GA)-based and Full-search algorithms in terms of decreasing the number of MSE computations. The number of MSE computations was reduced by the proposed algorithm for 463 times faster compared to the Full-search algorithm, although the retrieved image quality did not have a considerable change.

  6. Empirical gradient threshold technique for automated segmentation across image modalities and cell lines.

    Science.gov (United States)

    Chalfoun, J; Majurski, M; Peskin, A; Breen, C; Bajcsy, P; Brady, M

    2015-10-01

    New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21,000×21,000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference

  7. Improved medical image modality classification using a combination of visual and textual features.

    Science.gov (United States)

    Dimitrovski, Ivica; Kocev, Dragi; Kitanovski, Ivan; Loskovska, Suzana; Džeroski, Sašo

    2015-01-01

    In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and 2013, described by four visual and one textual types of features, and combinations thereof. We used local binary patterns, color and edge directivity descriptors, fuzzy color and texture histogram and scale-invariant feature transform (and its variant opponentSIFT) as visual features and the standard bag-of-words textual representation coupled with TF-IDF weighting. The results from the extensive experimental evaluation identify the SIFT and opponentSIFT features as the best performing features for modality classification. Next, the low-level fusion of the visual features improves the predictive performance of the classifiers. This is because the different features are able to capture different aspects of an image, their combination offering a more complete representation of the visual content in an image. Moreover, adding textual features further increases the predictive performance. Finally, the results obtained with our approach are the best results reported on these databases so far. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Study and analysis of wavelet based image compression techniques

    African Journals Online (AJOL)

    user

    Discrete Wavelet Transform (DWT) is a recently developed compression ... serve emerging areas of mobile multimedia and internet communication, ..... In global thresholding the best trade-off between PSNR and compression is provided by.

  9. Novelty detection of foreign objects in food using multi-modal X-ray imaging

    DEFF Research Database (Denmark)

    Einarsdottir, Hildur; Emerson, Monica Jane; Clemmensen, Line Katrine Harder

    2016-01-01

    In this paper we demonstrate a method for novelty detection of foreign objects in food products using grating-based multimodal X-ray imaging. With this imaging technique three modalities are available with pixel correspondence, enhancing organic materials such as wood chips, insects and soft...... plastics not detectable by conventional X-ray absorption radiography. We conduct experiments, where several food products are imaged with common foreign objects typically found in the food processing industry. To evaluate the benefit from using this multi-contrast X-ray technique over conventional X......-ray absorption imaging, a novelty detection scheme based on well known image- and statistical analysis techniques is proposed. The results show that the presented method gives superior recognition results and highlights the advantage of grating-based imaging....

  10. Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

    Science.gov (United States)

    Li, Xianye; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2018-03-01

    A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

  11. A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map

    International Nuclear Information System (INIS)

    Xiao Di; Cai Hong-Kun; Zheng Hong-Ying

    2015-01-01

    In this paper, a compressive sensing (CS) and chaotic map-based joint image encryption and watermarking algorithm is proposed. The transform domain coefficients of the original image are scrambled by Arnold map firstly. Then the watermark is adhered to the scrambled data. By compressive sensing, a set of watermarked measurements is obtained as the watermarked cipher image. In this algorithm, watermark embedding and data compression can be performed without knowing the original image; similarly, watermark extraction will not interfere with decryption. Due to the characteristics of CS, this algorithm features compressible cipher image size, flexible watermark capacity, and lossless watermark extraction from the compressed cipher image as well as robustness against packet loss. Simulation results and analyses show that the algorithm achieves good performance in the sense of security, watermark capacity, extraction accuracy, reconstruction, robustness, etc. (paper)

  12. MO-AB-BRA-02: A Novel Scatter Imaging Modality for Real-Time Image Guidance During Lung SBRT

    International Nuclear Information System (INIS)

    Redler, G; Bernard, D; Templeton, A; Chu, J; Nair, C Kumaran; Turian, J

    2015-01-01

    Purpose: A novel scatter imaging modality is developed and its feasibility for image-guided radiation therapy (IGRT) during stereotactic body radiation therapy (SBRT) for lung cancer patients is assessed using analytic and Monte Carlo models as well as experimental testing. Methods: During treatment, incident radiation interacts and scatters from within the patient. The presented methodology forms an image of patient anatomy from the scattered radiation for real-time localization of the treatment target. A radiographic flat panel-based pinhole camera provides spatial information regarding the origin of detected scattered radiation. An analytical model is developed, which provides a mathematical formalism for describing the scatter imaging system. Experimental scatter images are acquired by irradiating an object using a Varian TrueBeam accelerator. The differentiation between tissue types is investigated by imaging simple objects of known compositions (water, lung, and cortical bone equivalent). A lung tumor phantom, simulating materials and geometry encountered during lung SBRT treatments, is fabricated and imaged to investigate image quality for various quantities of delivered radiation. Monte Carlo N-Particle (MCNP) code is used for validation and testing by simulating scatter image formation using the experimental pinhole camera setup. Results: Analytical calculations, MCNP simulations, and experimental results when imaging the water, lung, and cortical bone equivalent objects show close agreement, thus validating the proposed models and demonstrating that scatter imaging differentiates these materials well. Lung tumor phantom images have sufficient contrast-to-noise ratio (CNR) to clearly distinguish tumor from surrounding lung tissue. CNR=4.1 and CNR=29.1 for 10MU and 5000MU images (equivalent to 0.5 and 250 second images), respectively. Conclusion: Lung SBRT provides favorable treatment outcomes, but depends on accurate target localization. A comprehensive

  13. MO-AB-BRA-02: A Novel Scatter Imaging Modality for Real-Time Image Guidance During Lung SBRT

    Energy Technology Data Exchange (ETDEWEB)

    Redler, G; Bernard, D; Templeton, A; Chu, J [Rush University Medical Center, Chicago, IL (United States); Nair, C Kumaran [University of Chicago, Chicago, IL (United States); Turian, J [Rush University Medical Center, Chicago, IL (United States); Rush Radiosurgery LLC, Chicago, IL (United States)

    2015-06-15

    Purpose: A novel scatter imaging modality is developed and its feasibility for image-guided radiation therapy (IGRT) during stereotactic body radiation therapy (SBRT) for lung cancer patients is assessed using analytic and Monte Carlo models as well as experimental testing. Methods: During treatment, incident radiation interacts and scatters from within the patient. The presented methodology forms an image of patient anatomy from the scattered radiation for real-time localization of the treatment target. A radiographic flat panel-based pinhole camera provides spatial information regarding the origin of detected scattered radiation. An analytical model is developed, which provides a mathematical formalism for describing the scatter imaging system. Experimental scatter images are acquired by irradiating an object using a Varian TrueBeam accelerator. The differentiation between tissue types is investigated by imaging simple objects of known compositions (water, lung, and cortical bone equivalent). A lung tumor phantom, simulating materials and geometry encountered during lung SBRT treatments, is fabricated and imaged to investigate image quality for various quantities of delivered radiation. Monte Carlo N-Particle (MCNP) code is used for validation and testing by simulating scatter image formation using the experimental pinhole camera setup. Results: Analytical calculations, MCNP simulations, and experimental results when imaging the water, lung, and cortical bone equivalent objects show close agreement, thus validating the proposed models and demonstrating that scatter imaging differentiates these materials well. Lung tumor phantom images have sufficient contrast-to-noise ratio (CNR) to clearly distinguish tumor from surrounding lung tissue. CNR=4.1 and CNR=29.1 for 10MU and 5000MU images (equivalent to 0.5 and 250 second images), respectively. Conclusion: Lung SBRT provides favorable treatment outcomes, but depends on accurate target localization. A comprehensive

  14. A Near-Lossless Image Compression Algorithm Suitable for Hardware Design in Wireless Endoscopy System

    Directory of Open Access Journals (Sweden)

    Xie Xiang

    2007-01-01

    Full Text Available In order to decrease the communication bandwidth and save the transmitting power in the wireless endoscopy capsule, this paper presents a new near-lossless image compression algorithm based on the Bayer format image suitable for hardware design. This algorithm can provide low average compression rate ( bits/pixel with high image quality (larger than dB for endoscopic images. Especially, it has low complexity hardware overhead (only two line buffers and supports real-time compressing. In addition, the algorithm can provide lossless compression for the region of interest (ROI and high-quality compression for other regions. The ROI can be selected arbitrarily by varying ROI parameters. In addition, the VLSI architecture of this compression algorithm is also given out. Its hardware design has been implemented in m CMOS process.

  15. Dermatological Feasibility of Multimodal Facial Color Imaging Modality for Cross-Evaluation of Facial Actinic Keratosis

    Science.gov (United States)

    Bae, Youngwoo; Son, Taeyoon; Nelson, J. Stuart; Kim, Jae-Hong; Choi, Eung Ho; Jung, Byungjo

    2010-01-01

    Background/Purpose Digital color image analysis is currently considered as a routine procedure in dermatology. In our previous study, a multimodal facial color imaging modality (MFCIM), which provides a conventional, parallel- and cross-polarization, and fluorescent color image, was introduced for objective evaluation of various facial skin lesions. This study introduces a commercial version of MFCIM, DermaVision-PRO, for routine clinical use in dermatology and demonstrates its dermatological feasibility for cross-evaluation of skin lesions. Methods/Results Sample images of subjects with actinic keratosis or non-melanoma skin cancers were obtained at four different imaging modes. Various image analysis methods were applied to cross-evaluate the skin lesion and, finally, extract valuable diagnostic information. DermaVision-PRO is potentially a useful tool as an objective macroscopic imaging modality for quick prescreening and cross-evaluation of facial skin lesions. Conclusion DermaVision-PRO may be utilized as a useful tool for cross-evaluation of widely distributed facial skin lesions and an efficient database management of patient information. PMID:20923462

  16. Cloud solution for histopathological image analysis using region of interest based compression.

    Science.gov (United States)

    Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

    2017-07-01

    Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

  17. Optical image encryption scheme with multiple light paths based on compressive ghost imaging

    Science.gov (United States)

    Zhu, Jinan; Yang, Xiulun; Meng, Xiangfeng; Wang, Yurong; Yin, Yongkai; Sun, Xiaowen; Dong, Guoyan

    2018-02-01

    An optical image encryption method with multiple light paths is proposed based on compressive ghost imaging. In the encryption process, M random phase-only masks (POMs) are generated by means of logistic map algorithm, and these masks are then uploaded to the spatial light modulator (SLM). The collimated laser light is divided into several beams by beam splitters as it passes through the SLM, and the light beams illuminate the secret images, which are converted into sparse images by discrete wavelet transform beforehand. Thus, the secret images are simultaneously encrypted into intensity vectors by ghost imaging. The distances between the SLM and secret images vary and can be used as the main keys with original POM and the logistic map algorithm coefficient in the decryption process. In the proposed method, the storage space can be significantly decreased and the security of the system can be improved. The feasibility, security and robustness of the method are further analysed through computer simulations.

  18. Block-Based Compressed Sensing for Neutron Radiation Image Using WDFB

    Directory of Open Access Journals (Sweden)

    Wei Jin

    2015-01-01

    Full Text Available An ideal compression method for neutron radiation image should have high compression ratio while keeping more details of the original image. Compressed sensing (CS, which can break through the restrictions of sampling theorem, is likely to offer an efficient compression scheme for the neutron radiation image. Combining wavelet transform with directional filter banks, a novel nonredundant multiscale geometry analysis transform named Wavelet Directional Filter Banks (WDFB is constructed and applied to represent neutron radiation image sparsely. Then, the block-based CS technique is introduced and a high performance CS scheme for neutron radiation image is proposed. By performing two-step iterative shrinkage algorithm the problem of L1 norm minimization is solved to reconstruct neutron radiation image from random measurements. The experiment results demonstrate that the scheme not only improves the quality of reconstructed image obviously but also retains more details of original image.

  19. High bit depth infrared image compression via low bit depth codecs

    Science.gov (United States)

    Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

    2017-08-01

    Future infrared remote sensing systems, such as monitoring of the Earth's environment by satellites, infrastructure inspection by unmanned airborne vehicles etc., will require 16 bit depth infrared images to be compressed and stored or transmitted for further analysis. Such systems are equipped with low power embedded platforms where image or video data is compressed by a hardware block called the video processing unit (VPU). However, in many cases using two 8-bit VPUs can provide advantages compared with using higher bit depth image compression directly. We propose to compress 16 bit depth images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed by an image or video codec with 8 bits per pixel input format. We analyze how the compression parameters for both MSB and LSB images should be chosen to provide the maximum objective quality for a given compression ratio. Finally, we apply the proposed infrared image compression method utilizing JPEG and H.264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can achieve similar result as 16 bit HEVC codec.

  20. Image compression-encryption algorithms by combining hyper-chaotic system with discrete fractional random transform

    Science.gov (United States)

    Gong, Lihua; Deng, Chengzhi; Pan, Shumin; Zhou, Nanrun

    2018-07-01

    Based on hyper-chaotic system and discrete fractional random transform, an image compression-encryption algorithm is designed. The original image is first transformed into a spectrum by the discrete cosine transform and the resulting spectrum is compressed according to the method of spectrum cutting. The random matrix of the discrete fractional random transform is controlled by a chaotic sequence originated from the high dimensional hyper-chaotic system. Then the compressed spectrum is encrypted by the discrete fractional random transform. The order of DFrRT and the parameters of the hyper-chaotic system are the main keys of this image compression and encryption algorithm. The proposed algorithm can compress and encrypt image signal, especially can encrypt multiple images once. To achieve the compression of multiple images, the images are transformed into spectra by the discrete cosine transform, and then the spectra are incised and spliced into a composite spectrum by Zigzag scanning. Simulation results demonstrate that the proposed image compression and encryption algorithm is of high security and good compression performance.

  1. A Coded Aperture Compressive Imaging Array and Its Visual Detection and Tracking Algorithms for Surveillance Systems

    Directory of Open Access Journals (Sweden)

    Hanxiao Wu

    2012-10-01

    Full Text Available In this paper, we propose an application of a compressive imaging system to the problem of wide-area video surveillance systems. A parallel coded aperture compressive imaging system is proposed to reduce the needed high resolution coded mask requirements and facilitate the storage of the projection matrix. Random Gaussian, Toeplitz and binary phase coded masks are utilized to obtain the compressive sensing images. The corresponding motion targets detection and tracking algorithms directly using the compressive sampling images are developed. A mixture of Gaussian distribution is applied in the compressive image space to model the background image and for foreground detection. For each motion target in the compressive sampling domain, a compressive feature dictionary spanned by target templates and noises templates is sparsely represented. An l1 optimization algorithm is used to solve the sparse coefficient of templates. Experimental results demonstrate that low dimensional compressed imaging representation is sufficient to determine spatial motion targets. Compared with the random Gaussian and Toeplitz phase mask, motion detection algorithms using a random binary phase mask can yield better detection results. However using random Gaussian and Toeplitz phase mask can achieve high resolution reconstructed image. Our tracking algorithm can achieve a real time speed that is up to 10 times faster than that of the l1 tracker without any optimization.

  2. Fast hybrid fractal image compression using an image feature and neural network

    International Nuclear Information System (INIS)

    Zhou Yiming; Zhang Chao; Zhang Zengke

    2008-01-01

    Since fractal image compression could maintain high-resolution reconstructed images at very high compression ratio, it has great potential to improve the efficiency of image storage and image transmission. On the other hand, fractal image encoding is time consuming for the best matching search between range blocks and domain blocks, which limits the algorithm to practical application greatly. In order to solve this problem, two strategies are adopted to improve the fractal image encoding algorithm in this paper. Firstly, based on the definition of an image feature, a necessary condition of the best matching search and FFC algorithm are proposed, and it could reduce the search space observably and exclude most inappropriate domain blocks according to each range block before the best matching search. Secondly, on the basis of FFC algorithm, in order to reduce the mapping error during the best matching search, a special neural network is constructed to modify the mapping scheme for the subblocks, in which the pixel values fluctuate greatly (FNFC algorithm). Experimental results show that the proposed algorithms could obtain good quality of the reconstructed images and need much less time than the baseline encoding algorithm

  3. Feasibility of intermittent pneumatic compression for venous thromboembolism prophylaxis during magnetic resonance imaging-guided interventions

    Energy Technology Data Exchange (ETDEWEB)

    Maybody, Majid, E-mail: maybodym@mskcc.org [Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 (United States); Taslakian, Bedros, E-mail: bt05@aub.edu.lb [Department of Diagnostic Radiology, American University of Beirut Medical Center, Riad El-Solh, 1107 2020 Beirut (Lebanon); Durack, Jeremy C., E-mail: durackj@mskcc.org [Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 (United States); Kaye, Elena A., E-mail: kayee@mskcc.org [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 (United States); Erinjeri, Joseph P., E-mail: erinjerj@mskcc.org [Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 (United States); Srimathveeravalli, Govindarajan, E-mail: srimaths@mskcc.org [Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 (United States); Solomon, Stephen B., E-mail: solomons@mskcc.org [Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 (United States)

    2015-04-15

    Highlights: •The controller of a standard SCD is labeled as an “MR-unsafe”. •No commercially available “MR-safe” SCDs. •Standard SCDs can be used in iMRI by placing the device outside the MRI scanner room. •Using serial extension tubing did not cause device failure. -- Abstract: Purpose: Venous thromboembolism (VTE) is a common cause of morbidity and mortality in hospitalized and surgical patients. To reduce risk, perioperative VTE prophylaxis is recommended for cancer patients undergoing surgical or interventional procedures. Magnetic resonance imaging (MRI) is increasingly used in interventional oncology when alternative imaging modalities do not adequately delineate malignancies. Extended periods of immobilization during MRI-guided interventions necessitate an MR compatible sequential compression device (SCD) for intra-procedural mechanical VTE prophylaxis. Such devices are not commercially available. Materials and methods: A standard SCD routinely used at our institution for VTE prophylaxis during interventional procedures was used. To satisfy MR safety requirements, the SCD controller was placed in the MR control room and connected to the compression sleeves in the magnet room through the wave guide using tubing extensions. The controller pressure sensor was used to monitor adequate pressure delivery and detect ineffective low or abnormal high pressure delivery. VTE prophylaxis was provided using the above mentioned device for 38 patients undergoing MR-guided ablations. Results: There was no evidence of device failure due to loss of pressure in the extension tubing assembly. No interference with the anesthesia or interventional procedures was documented. Conclusion: Although the controller of a standard SCD is labeled as “MR-unsafe”, the SCD can be used in interventional MR settings by placing the device outside the MR scanner room. Using serial tubing extensions did not cause device failure. The described method can be used to provide

  4. High bit depth infrared image compression via low bit depth codecs

    DEFF Research Database (Denmark)

    Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

    2017-01-01

    images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed.......264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can...

  5. The wavelet/scalar quantization compression standard for digital fingerprint images

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, J.N.; Brislawn, C.M.

    1994-04-01

    A new digital image compression standard has been adopted by the US Federal Bureau of Investigation for use on digitized gray-scale fingerprint images. The algorithm is based on adaptive uniform scalar quantization of a discrete wavelet transform image decomposition and is referred to as the wavelet/scalar quantization standard. The standard produces archival quality images at compression ratios of around 20:1 and will allow the FBI to replace their current database of paper fingerprint cards with digital imagery.

  6. Image and video compression for multimedia engineering fundamentals, algorithms, and standards

    CERN Document Server

    Shi, Yun Q

    2008-01-01

    Part I: Fundamentals Introduction Quantization Differential Coding Transform Coding Variable-Length Coding: Information Theory Results (II) Run-Length and Dictionary Coding: Information Theory Results (III) Part II: Still Image Compression Still Image Coding: Standard JPEG Wavelet Transform for Image Coding: JPEG2000 Nonstandard Still Image Coding Part III: Motion Estimation and Compensation Motion Analysis and Motion Compensation Block Matching Pel-Recursive Technique Optical Flow Further Discussion and Summary on 2-D Motion Estimation Part IV: Video Compression Fundam

  7. A new procedure of modal parameter estimation for high-speed digital image correlation

    Science.gov (United States)

    Huňady, Róbert; Hagara, Martin

    2017-09-01

    The paper deals with the use of 3D digital image correlation in determining modal parameters of mechanical systems. It is a non-contact optical method, which for the measurement of full-field spatial displacements and strains of bodies uses precise digital cameras with high image resolution. Most often this method is utilized for testing of components or determination of material properties of various specimens. In the case of using high-speed cameras for measurement, the correlation system is capable of capturing various dynamic behaviors, including vibration. This enables the potential use of the mentioned method in experimental modal analysis. For that purpose, the authors proposed a measuring chain for the correlation system Q-450 and developed a software application called DICMAN 3D, which allows the direct use of this system in the area of modal testing. The created application provides the post-processing of measured data and the estimation of modal parameters. It has its own graphical user interface, in which several algorithms for the determination of natural frequencies, mode shapes and damping of particular modes of vibration are implemented. The paper describes the basic principle of the new estimation procedure which is crucial in the light of post-processing. Since the FRF matrix resulting from the measurement is usually relatively large, the estimation of modal parameters directly from the FRF matrix may be time-consuming and may occupy a large part of computer memory. The procedure implemented in DICMAN 3D provides a significant reduction in memory requirements and computational time while achieving a high accuracy of modal parameters. Its computational efficiency is particularly evident when the FRF matrix consists of thousands of measurement DOFs. The functionality of the created software application is presented on a practical example in which the modal parameters of a composite plate excited by an impact hammer were determined. For the

  8. Model-Based Photoacoustic Image Reconstruction using Compressed Sensing and Smoothed L0 Norm

    OpenAIRE

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-01-01

    Photoacoustic imaging (PAI) is a novel medical imaging modality that uses the advantages of the spatial resolution of ultrasound imaging and the high contrast of pure optical imaging. Analytical algorithms are usually employed to reconstruct the photoacoustic (PA) images as a result of their simple implementation. However, they provide a low accurate image. Model-based (MB) algorithms are used to improve the image quality and accuracy while a large number of transducers and data acquisition a...

  9. Effect of CT digital image compression on detection of coronary artery calcification

    International Nuclear Information System (INIS)

    Zheng, L.M.; Sone, S.; Itani, Y.; Wang, Q.; Hanamura, K.; Asakura, K.; Li, F.; Yang, Z.G.; Wang, J.C.; Funasaka, T.

    2000-01-01

    Purpose: To test the effect of digital compression of CT images on the detection of small linear or spotted high attenuation lesions such as coronary artery calcification (CAC). Material and methods: Fifty cases with and 50 without CAC were randomly selected from a population that had undergone spiral CT of the thorax for screening lung cancer. CT image data were compressed using JPEG (Joint Photographic Experts Group) or wavelet algorithms at ratios of 10:1, 20:1 or 40:1. Five radiologists reviewed the uncompressed and compressed images on a cathode-ray-tube. Observer performance was evaluated with receiver operating characteristic analysis. Results: CT images compressed at a ratio as high as 20:1 were acceptable for primary diagnosis of CAC. There was no significant difference in the detection accuracy for CAC between JPEG and wavelet algorithms at the compression ratios up to 20:1. CT images were more vulnerable to image blurring on the wavelet compression at relatively lower ratios, and 'blocking' artifacts occurred on the JPEG compression at relatively higher ratios. Conclusion: JPEG and wavelet algorithms allow compression of CT images without compromising their diagnostic value at ratios up to 20:1 in detecting small linear or spotted high attenuation lesions such as CAC, and there was no difference between the two algorithms in diagnostic accuracy

  10. Effect of high image compression on the reproducibility of cardiac Sestamibi reporting

    International Nuclear Information System (INIS)

    Thomas, P.; Allen, L.; Beuzeville, S.

    1999-01-01

    Full text: Compression algorithms have been mooted to minimize storage space and transmission times of digital images. We assessed the impact of high-level lousy compression using JPEG and wavelet algorithms on image quality and reporting accuracy of cardiac Sestamibi studies. Twenty stress/rest Sestamibi cardiac perfusion studies were reconstructed into horizontal short, vertical long and horizontal long axis slices using conventional methods. Each of these six sets of slices were aligned for reporting and saved (uncompressed) as a bitmap. This bitmap was then compressed using JPEG compression, then decompressed and saved as a bitmap for later viewing. This process was repeated using the original bitmap and wavelet compression. Finally, a second copy of the original bitmap was made. All 80 bitmaps were randomly coded to ensure blind reporting. The bitmaps were read blinded and by consensus of 2 experienced nuclear medicine physicians using a 5-point scale and 25 cardiac segments. Subjective image quality was also reported using a 3-point scale. Samples of the compressed images were also subtracted from the original bitmap for visual comparison of differences. Results showed an average compression ratio of 23:1 for wavelet and 13:1 for JPEG. Image subtraction showed only very minor discordance between the original and compressed images. There was no significant difference in subjective quality between the compressed and uncompressed images. There was no significant difference in reporting reproducibility of the identical bitmap copy, the JPEG image and the wavelet image compared with the original bitmap. Use of the high compression algorithms described had no significant impact on reporting reproducibility and subjective image quality of cardiac Sestamibi perfusion studies

  11. Costs, charges, and revenues for hospital diagnostic imaging procedures: differences by modality and hospital characteristics.

    Science.gov (United States)

    Sistrom, Christopher Lee; McKay, Niccie L

    2005-06-01

    This study examined financial data reported by Florida hospitals concerning costs, charges, and revenues related to imaging services. Financial reports to the Florida Hospital Uniform Reporting System by all licensed acute care facilities for fiscal year 2002 were used to calculate four financial indices on a per procedure basis. These included charge, net revenue, operating expense (variable cost), and contribution margin. Analysis, stratified by cost center (imaging modality), tested the effects of bed size, ownership, teaching status, and urban or rural status on the four indices. The mean operating expense and charge per procedure were as follows: computed tomography (CT): $51 and $1565; x-ray and ultrasound: $55 and $410; nuclear medicine (NM): $135 and $1138; and magnetic resonance imaging (MRI): $165 and $2048. With all four modalities, for-profit hospitals had higher charges than not-for-profit and public facilities. Excepting NM, however, the difference by ownership disappeared when considering net revenue. Operating expense did not differ by ownership type or bed size. Operating expense (variable cost) per procedure is considerably lower for CT than for MRI. Consequently, when diagnostically equivalent, CT is preferable to MRI in terms of costs for hospitals. If the cost structure of nonhospital imaging is at all similar to hospitals, the profit potential for performing CT and MRI seems to be substantial, which has relevance to the issue of imaging self-referral.

  12. Interactive, multi-modality image registrations for combined MRI/MRSI-planned HDR prostate brachytherapy

    Directory of Open Access Journals (Sweden)

    Galen Reed

    2011-03-01

    Full Text Available Purpose: This study presents the steps and criteria involved in the series of image registrations used clinically during the planning and dose delivery of focal high dose-rate (HDR brachytherapy of the prostate. Material and methods: Three imaging modalities – Magnetic Resonance Imaging (MRI, Magnetic Resonance Spectroscopic Imaging (MRSI, and Computed Tomography (CT – were used at different steps during the process. MRSI is used for identification of dominant intraprosatic lesions (DIL. A series of rigid and nonrigid transformations were applied to the data to correct for endorectal-coil-induced deformations and for alignment with the planning CT. Mutual information was calculated as a morphing metric. An inverse planning optimization algorithm was applied to boost dose to the DIL while providing protection to the urethra, penile bulb, rectum, and bladder. Six prostate cancer patients were treated using this protocol. Results: The morphing algorithm successfully modeled the probe-induced prostatic distortion. Mutual information calculated between the morphed images and images acquired without the endorectal probe showed a significant (p = 0.0071 increase to that calculated between the unmorphed images and images acquired without the endorectal probe. Both mutual information and visual inspection serve as effective diagnostics of image morphing. The entire procedure adds less than thirty minutes to the treatment planning. Conclusion: This work demonstrates the utility of image transformations and registrations to HDR brachytherapy of prostate cancer.

  13. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

    Science.gov (United States)

    Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

    2015-01-01

    The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

  14. Comparing Image Perception of Bladder Tumors in Four Different Storz Professional Image Enhancement System Modalities Using the íSPIES App

    NARCIS (Netherlands)

    Kamphuis, Guido M.; de Bruin, D. Martijn; Brandt, Martin J.; Knoll, Thomas; Conort, Pierre; Lapini, Alberto; Dominguez-Escrig, Jose L.; de La Rosette, Jean J. M. C. H.

    2016-01-01

    To evaluate the variation of interpretation of the same bladder urothelium image in different Storz Professional Image Enhancement System (SPIES) modalities. SPIES contains a White light (WL), Spectra A (SA), Spectra B (SB), and Clara and Chroma combined (CC) modality. An App for the iPAD retina was

  15. Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images

    Directory of Open Access Journals (Sweden)

    Christian Schou Oxvig

    2014-10-01

    Full Text Available Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also provides researchers in compressed sensing with a selection of algorithms for reconstructing undersampled general images, and offers a consistent and rigorous way to efficiently evaluate the researchers own developed reconstruction algorithms in terms of phase transitions. The package also serves as a convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research.

  16. Compressed Sensing and Low-Rank Matrix Decomposition in Multisource Images Fusion

    Directory of Open Access Journals (Sweden)

    Kan Ren

    2014-01-01

    Full Text Available We propose a novel super-resolution multisource images fusion scheme via compressive sensing and dictionary learning theory. Under the sparsity prior of images patches and the framework of the compressive sensing theory, the multisource images fusion is reduced to a signal recovery problem from the compressive measurements. Then, a set of multiscale dictionaries are learned from several groups of high-resolution sample image’s patches via a nonlinear optimization algorithm. Moreover, a new linear weights fusion rule is proposed to obtain the high-resolution image. Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to its counterparts.

  17. Role of the multi-modality image archival and communication system in nuclear medicine

    International Nuclear Information System (INIS)

    Bela Kari; Adam Mester; Erno Mako; Zoltan Gyorfi; Bela Mihalik; Zsolt; Hegyi

    2004-01-01

    Various non-invasive imaging systems produce increasing amount of diagnostic images day by day in digital format. The direct consequence of this tendency places electronic archives and image transfers in spotlight. Moreover, the digital image archives may support any other activities like simultaneous displaying of multi-modality images, telediagnostics, on-line consultation, construction of standard databases for dedicated organs by regional and/or country wide (e.g. myocardial scintigraphy, mammography, etc....) in order to obtain much more exact diagnosis as well as to support education and training. Our institute started similar research and developing activities few years ago, resulting the construction of our PACS systems -MEDISA LINUX Debian and eRAD ImageMedical TM LINUX Red Hat- together with the telecommunication part. Mass storage unit of PACS is based on hard drives connecting in RAID with l.2Tbyte capacity. The on-line telecommunication system consists of an ISDN Multi-Media System (MMS) and Internet based independent units. MMS was dedicated mainly for on-line teleconferencing and consultation by the simultaneously transferred morphological and functional images obtaining from the central archives by DICOM or any other allowable image formats. MMS has been created as a part and requirements of an EU research project - RETRANSPLANT -. The central archives -PACS- can be accessed by DICOM 3.0 protocol on Internet surface through well maintained and secure access rights. Displaying and post-processing of any retrieved images on individual workstations are supported by eRAD ImageMedical TM PracticeBuilder1-2-3 (Window based) image manager with its unique supports and services. The 'real engine' of PracticeBuilder is Ver.5.0 or newer Internet Explorer. The unique feature of PracticelBuilder1-2-3 is the extremely fast patient and image access from the archives even from very 'far distance' (through continents), due to the exceptional image communication

  18. Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

    Science.gov (United States)

    Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

    2015-03-01

    Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

  19. Encryption of Stereo Images after Compression by Advanced Encryption Standard (AES

    Directory of Open Access Journals (Sweden)

    Marwah k Hussien

    2018-04-01

    Full Text Available New partial encryption schemes are proposed, in which a secure encryption algorithm is used to encrypt only part of the compressed data. Partial encryption applied after application of image compression algorithm. Only 0.0244%-25% of the original data isencrypted for two pairs of dif-ferent grayscale imageswiththe size (256 ´ 256 pixels. As a result, we see a significant reduction of time in the stage of encryption and decryption. In the compression step, the Orthogonal Search Algorithm (OSA for motion estimation (the dif-ferent between stereo images is used. The resulting disparity vector and the remaining image were compressed by Discrete Cosine Transform (DCT, Quantization and arithmetic encoding. The image compressed was encrypted by Advanced Encryption Standard (AES. The images were then decoded and were compared with the original images. Experimental results showed good results in terms of Peak Signal-to-Noise Ratio (PSNR, Com-pression Ratio (CR and processing time. The proposed partial encryption schemes are fast, se-cure and do not reduce the compression performance of the underlying selected compression methods

  20. Detection of relationships among multi-modal brain imaging meta-features via information flow.

    Science.gov (United States)

    Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

    2018-01-15

    Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is

  1. Telemedicine + OCT: toward design of optimized algorithms for high-quality compressed images

    Science.gov (United States)

    Mousavi, Mahta; Lurie, Kristen; Land, Julian; Javidi, Tara; Ellerbee, Audrey K.

    2014-03-01

    Telemedicine is an emerging technology that aims to provide clinical healthcare at a distance. Among its goals, the transfer of diagnostic images over telecommunication channels has been quite appealing to the medical community. When viewed as an adjunct to biomedical device hardware, one highly important consideration aside from the transfer rate and speed is the accuracy of the reconstructed image at the receiver end. Although optical coherence tomography (OCT) is an established imaging technique that is ripe for telemedicine, the effects of OCT data compression, which may be necessary on certain telemedicine platforms, have not received much attention in the literature. We investigate the performance and efficiency of several lossless and lossy compression techniques for OCT data and characterize their effectiveness with respect to achievable compression ratio, compression rate and preservation of image quality. We examine the effects of compression in the interferogram vs. A-scan domain as assessed with various objective and subjective metrics.

  2. Diagnostic accuracy of imaging modalities for internal derangements of temporomandibular joint

    International Nuclear Information System (INIS)

    Kobayashi, Kaoru; Igarashi, Chinami; Yuasa, Masao; Imanaka, Masahiro; Kondoh, Toshirou

    1998-01-01

    The purpose of this study was to evaluate and review the diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of imaging diagnosis for temporomandibular disorders. The role of diagnostic imaging is to detect and document specific anatomic abnormalities associated with the signs and symptoms in the temporomandibular joint. Magnetic resonance imaging (MR imaging) can accurately depict disc displacement and disc deformity. MR imaging is our first choice among the various imaging modalities for the patients with clinical signs and symptoms. However, it has been shown that intra-capsular adhesions and perforations of the disc and retrodiscal tissue are sometimes not detected by MR imaging. To improve the diagnostic technique for adhesions and perforations, double-contrast arthrotomography with fluoroscopy should be employed. The irregular surface of the eminences and the glenoid fossae shown by MR imaging and tomography are correlated with subchondral bone exposure by arthroscopy. Erosion of the condyles detected by MR imaging, tomography and rotational panoramic radiography is correlated with subchondral bone exposure detected by arthroscopy. (author). 69 refs

  3. On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

    Science.gov (United States)

    LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

    2017-12-01

    The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

  4. Detection ability of FDG-PET/CT comparing with other imaging modalities in multiple myeloma patients

    International Nuclear Information System (INIS)

    Chae, Min Jeong; Lee, Tae Hyun; Pai, Moon Sun; Cheon, Gi Jeong; Choi, Chang Woon; Lim, Sang Moo

    2007-01-01

    Multiple myeloma (MM) is characterized by bone marrow infiltration with malignant plasma cells. It is important to detect involving bone for diagnosis and management of MM. The aim of this study was to evaluate the diagnostic ability and limitation of 18F-FDG-PET/CT (PET/CT) comparing other imaging modalities (separated PET and CT, whole body plain X-ray (XR), bone scintigraphy (BS), and MRI) in MM. Twenty PET/CT scans were performed in 16 patients (M: F=6: 10, median age=59 y). PET/CT findings were compared with available other images (n of CT=21, XR=21, BS=8, and MRI=5). Concordance with more than 2 image modalities, laboratory data, symptom, and biopsies were used for diagnosis of detected lesions. PET/CT revealed 256 of total 287 sites (sensitivity, 89.2%; accuracy, 84.8%). The sensitivity and accuracy of separating PET, CT, and XR were 86.3%, 70.4%; 47.4%, 50.3%; and 72.8%, 72.4%, respectively. Available BS identified 67 of 202 sites (sensitivity, 33.2%; accuracy, 44.0%). MRI detected 20 of 24 sites (sensitivity, 83.3%; accuracy, 36.3%). False positive rate (FP) of PET, XR, and MRI was as high as 87.8%, 95.1%, and 100%. PET for rib lesion identified 9 of 10 patients (90.0%) but for skull lesion only 4 of 7 patients (57.2%) with underestimation. 5 patients in MRI showed diffuse marrow signal change but only 3 had marrow involvement. But PET/CT showed higher accuracy than MRI. PET/CT was the most useful tool for detecting involving bone of MM comparing with other imaging modalities. Moreover, PET/CT is expected to overcome the limitations for the small osteolytic bone lesions with diffuse FDG uptake on PET

  5. The Impact of Imaging Modality on the Measurement of Coronal Plane Alignment After Total Knee Arthroplasty.

    Science.gov (United States)

    Nam, Denis; Vajapey, Sravya; Nunley, Ryan M; Barrack, Robert L

    2016-10-01

    The optimal coronal alignment after total knee arthroplasty (TKA) has become an area of increased debate. Sources of variability among investigations include the radiographic technique used for both preoperative surgical planning and postoperative alignment assessments. This study's purpose was to assess the impact of the imaging modality used on the measurement of coronal plane alignment after TKA. A consecutive series of patients undergoing TKA using the same cruciate-retaining prosthesis were included for analysis. Postoperatively, all patients received both a rotationally controlled, scout computed tomography scan and a hip-knee-ankle (HKA) image using the EOS Imaging system (EOS Inc., Paris, France). Two, independent observers measured the HKA angle, and femoral and tibial component alignment from each image. After classifying overall and component alignment as neutral, varus, or valgus, 40.6% (65 of 160) of knees had a discordant alignment classification for HKA, 28.1% (45 of 160) for femoral component alignment, and 26.9% (43 of 160) for tibial component alignment between their computed tomography and EOS images. Overall, 24.4% (39 of 160) of patients had a HKA difference of ≥3° between the 2 images, whereas 18.8% (30 of 160) and 20.0% (32 of 160) of patients had a femoral and tibial component alignment difference of ≥2°, respectively. Significant differences are present when comparing 2 measurement techniques of mechanical alignment after TKA. The impact of imaging modality on postoperative assessments must be accounted for and be consistent when comparing the results of different investigations. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

    Science.gov (United States)

    Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

    2016-01-01

    In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the

  7. Lipid-coated iron oxide nanoparticles for dual-modal imaging of hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Liang J

    2017-03-01

    Full Text Available Jinying Liang,1–3 Xinxin Zhang,2 Yunqiu Miao,2 Juan Li,1 Yong Gan2 1Department of Pharmaceutics, China Pharmaceutical University, Nanjing, People’s Republic of China; 2Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, People’s Republic of China; 3School of Pharmacy, Xinxiang Medical University, Xinxiang, People’s Republic of China Abstract: The development of noninvasive imaging techniques for the accurate diagnosis of progressive hepatocellular carcinoma (HCC is of great clinical significance and has always been desired. Herein, a hepatocellular carcinoma cell-targeting fluorescent magnetic nanoparticle (NP was obtained by conjugating near-infrared fluorescence to the surface of Fe3O4 (NIRF-Fe3O4 NPs, followed by coating the lipids consisting of tumoral hepatocytes-targeting polymer (Gal-P123. This magnetic NP (GPC@NIRF-Fe3O4 with superparamagnetic behavior showed high stability and safety in physiological conditions. In addition, GPC@NIRF-Fe3O4 achieved more specific uptake of human liver cancer cells than free Fe3O4 NPs. Importantly, with superparamagnetic iron oxide and strong NIR absorbance, GPC@NIRF-Fe3O4 NPs demonstrate prominent tumor-contrasted imaging performance both on fluorescent and T2-weighted magnetic resonance (MR imaging modalities in a living body. The relative MR signal enhancement of GPC@NIRF-Fe3O4 NPs achieved 5.4-fold improvement compared with NIR-Fe3O4 NPs. Therefore, GPC@NIRF-Fe3O4 NPs may be potentially used as a candidate for dual-modal imaging of tumors with information covalidated and directly compared by combining fluorescence and MR imaging. Keywords: dual-imaging, magnetic resonance imaging, hepatocellular carcinoma, tumor-targeting

  8. Pornographic image recognition and filtering using incremental learning in compressed domain

    Science.gov (United States)

    Zhang, Jing; Wang, Chao; Zhuo, Li; Geng, Wenhao

    2015-11-01

    With the rapid development and popularity of the network, the openness, anonymity, and interactivity of networks have led to the spread and proliferation of pornographic images on the Internet, which have done great harm to adolescents' physical and mental health. With the establishment of image compression standards, pornographic images are mainly stored with compressed formats. Therefore, how to efficiently filter pornographic images is one of the challenging issues for information security. A pornographic image recognition and filtering method in the compressed domain is proposed by using incremental learning, which includes the following steps: (1) low-resolution (LR) images are first reconstructed from the compressed stream of pornographic images, (2) visual words are created from the LR image to represent the pornographic image, and (3) incremental learning is adopted to continuously adjust the classification rules to recognize the new pornographic image samples after the covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic images. The experimental results show that the proposed pornographic image recognition method using incremental learning has a higher recognition rate as well as costing less recognition time in the compressed domain.

  9. Endoscopic Tri-Modal Imaging (ETMI With Optical Magnification in the Detection of Barrett's Early Neoplasia

    Directory of Open Access Journals (Sweden)

    Sarmed S. Sami

    2014-01-01

    Full Text Available Early lesion detection and characterisation is vital to ensure accurate management in patients with gastrointestinal neoplasia. Endoscopic Tri-modal Imaging (ETMI technology has been shown to improve the targeted detection of early dysplastic lesions in Barrett's Oesophagus, but these results were not confirmed in non-expert hands [1]. This technology incorporates high resolution while light endoscopy (HRE, Auto Fluorescence Imaging (AFI and Narrow Band Imaging (NBI in one endoscope. The mucosa is first inspected with HRE, and then AFI is switched on to help in highlighting any suspicious areas in the mucosa [2]. These areas can be further examined by switching to NBI mode with magnification which helps to characterise mucosal patterns and identify early neoplasia [3].

  10. Improved MR imaging evaluation of chondromalacia patellae with use of a vise for cartilage compression

    International Nuclear Information System (INIS)

    Koenig, H.; Dinkelaker, F.; Wolf, K.J.

    1990-01-01

    This paper reports on earlier and more precise evaluation of chondromalacia patellae by means of MR imaging performed with a specially constructed vise for compression of the retropatellar cartilage. Two volunteers and 18 patients were examined 1-4 weeks before arthroscopy and cartilage biopsy. Imaging parameters included spin-echo (SE) (1,600/22 + 110 msec) and fast low-angle shot (FLASH) (30/12 msec, 10 degrees and 30 degrees excitation angles) sequences, 4-mm section thickness, and sagittal and axial views. For cartilage compression, we used a wooden vise. FLASH imaging was done without and with compression of the retropatellar cartilage. Cartilage thickness and signal intensities were measured

  11. A New Algorithm for the On-Board Compression of Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Raúl Guerra

    2018-03-01

    Full Text Available Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the earth’s surface. In this situation, an efficient compression of the hyperspectral images is mandatory in order to save bandwidth and storage space. Lossless compression algorithms have been traditionally preferred, in order to preserve all the information present in the hyperspectral cube for scientific purposes, despite their limited compression ratio. Nevertheless, the increment in the data-rate of the new-generation sensors is making more critical the necessity of obtaining higher compression ratios, making it necessary to use lossy compression techniques. A new transform-based lossy compression algorithm, namely Lossy Compression Algorithm for Hyperspectral Image Systems (HyperLCA, is proposed in this manuscript. This compressor has been developed for achieving high compression ratios with a good compression performance at a reasonable computational burden. An extensive amount of experiments have been performed in order to evaluate the goodness of the proposed HyperLCA compressor using different calibrated and uncalibrated hyperspectral images from the AVIRIS and Hyperion sensors. The results provided by the proposed HyperLCA compressor have been evaluated and compared against those produced by the most relevant state-of-the-art compression solutions. The theoretical and experimental evidence indicates that the proposed algorithm represents an excellent option for lossy compressing hyperspectral images, especially for applications where the available computational resources are limited, such as on-board scenarios.

  12. A tri-modal molecular imaging agent for sentinel lymph node mapping

    International Nuclear Information System (INIS)

    Qin, Zhengtao; Hoh, Carl K.; Hall, David J.; Vera, David R.

    2015-01-01

    Introduction: We report an “instant kit” method to radiolabel fluorescent-tilmanocept with 68 Ga and 99m Tc for tri-modal molecular imaging of sentinel lymph nodes (SLNs). Methods: Solutions of sodium acetate, 68 GaCl 3 and Na 99m TcO 4 were added successively to a “kit vial” containing lyophilized 800CW-tilmanocept, SnCl 2 , trehalose and ascorbic acid. After a 30-min incubation, the pH was neutralized with PBS. No purification was required. Radiochemical and fluorescence purity was measured by HPLC and ITLC techniques. In vitro stability was measured by standing gel chromatography (SGC) and ITLC by a 100-fold dilution 0.25 h after radiolabeling. In vivo stability was measured by SGC and ITLC after an 11 h incubation in human plasma. A dose (0.1 nmol, ~ 1 MBq 68 Ga, ~ 25 MBq 99m Tc) was injected to the footpad of 4 mice. Popliteal SLNs were imaged by PET and fluorescence imaging systems at 0.5, 24, 48, 72 h, then excised and assayed for 99m Tc. Results: Radiochemical and fluorescent purity exceeded 98%. The in vitro stability assay demonstrated high irreversibility of both radiolabels and the fluorescent label, and in vivo stability assay demonstrated high stability of the technetium and fluorescent labels to plasma metabolism. Popliteal SLNs were identified by PET and fluorescence imaging within 0.5 h of injection. SLN fluorescence intensity remained constant for 72 h, when ~ 1% of the injected dose resided in the SLN. Conclusions: Fluorescent-labeled tilmanocept can be radiolabeled with 68 Ga and 99m Tc by the sequential addition of each generator eluate to a lyophilized kit. The resulting tri-modal agent provides: PET images for pre-operative SLN mapping, fluorescence imaging up to 72 hours after injection, and quantitative radiometric measurement of SLN accumulation after excision.

  13. MR imaging of spinal factors and compression of the spinal cord in cervical myelopathy

    International Nuclear Information System (INIS)

    Kokubun, Shoichi; Ozawa, Hiroshi; Sakurai, Minoru; Ishii, Sukenobu; Tani, Shotaro; Sato, Tetsuaki.

    1992-01-01

    Magnetic resonance (MR) images of surgical 109 patients with cervical spondylotic myelopathy were retrospectively reviewed to examine whether MR imaging would replace conventional radiological procedures in determining spinal factors and spinal cord compression in this disease. MR imaging was useful in determining spondylotic herniation, continuous type of ossification of posterior longitudinal ligament, and calcification of yellow ligament, probably replacing CT myelography, discography, and CT discography. When total defect of the subarachnoid space on T2-weighted images and block on myelograms were compared in determining spinal cord compression, the spinal cord was affected more extensively by 1.3 intervertebral distance (IVD) on T2-weighted images. When indentation of one third or more in anterior and posterior diameter of the spinal cord was used as spinal cord compression, the difference in the affected extension between myelography and MR imaging was 0.2 IVD on T1-weighted images and 0.6 IVD on T2-weighted images. However, when block was seen in 3 or more IVD on myelograms, the range of spinal cord compression tended to be larger on T1-weighted images. For a small range of spinal cord compression, T1-weighted imaging seems to be helpful in determining the range of decompression. When using T2-weighted imaging, the range of decompression becomes large, frequently including posterior decompression. (N.K.)

  14. Undersampling strategies for compressed sensing accelerated MR spectroscopic imaging

    Science.gov (United States)

    Vidya Shankar, Rohini; Hu, Houchun Harry; Bikkamane Jayadev, Nutandev; Chang, John C.; Kodibagkar, Vikram D.

    2017-03-01

    Compressed sensing (CS) can accelerate magnetic resonance spectroscopic imaging (MRSI), facilitating its widespread clinical integration. The objective of this study was to assess the effect of different undersampling strategy on CS-MRSI reconstruction quality. Phantom data were acquired on a Philips 3 T Ingenia scanner. Four types of undersampling masks, corresponding to each strategy, namely, low resolution, variable density, iterative design, and a priori were simulated in Matlab and retrospectively applied to the test 1X MRSI data to generate undersampled datasets corresponding to the 2X - 5X, and 7X accelerations for each type of mask. Reconstruction parameters were kept the same in each case(all masks and accelerations) to ensure that any resulting differences can be attributed to the type of mask being employed. The reconstructed datasets from each mask were statistically compared with the reference 1X, and assessed using metrics like the root mean square error and metabolite ratios. Simulation results indicate that both the a priori and variable density undersampling masks maintain high fidelity with the 1X up to five-fold acceleration. The low resolution mask based reconstructions showed statistically significant differences from the 1X with the reconstruction failing at 3X, while the iterative design reconstructions maintained fidelity with the 1X till 4X acceleration. In summary, a pilot study was conducted to identify an optimal sampling mask in CS-MRSI. Simulation results demonstrate that the a priori and variable density masks can provide statistically similar results to the fully sampled reference. Future work would involve implementing these two masks prospectively on a clinical scanner.

  15. An Image Compression Scheme in Wireless Multimedia Sensor Networks Based on NMF

    Directory of Open Access Journals (Sweden)

    Shikang Kong

    2017-02-01

    Full Text Available With the goal of addressing the issue of image compression in wireless multimedia sensor networks with high recovered quality and low energy consumption, an image compression and transmission scheme based on non-negative matrix factorization (NMF is proposed in this paper. First, the NMF algorithm theory is studied. Then, a collaborative mechanism of image capture, block, compression and transmission is completed. Camera nodes capture images and send them to ordinary nodes which use an NMF algorithm for image compression. Compressed images are transmitted to the station by the cluster head node and received from ordinary nodes. The station takes on the image restoration. Simulation results show that, compared with the JPEG2000 and singular value decomposition (SVD compression schemes, the proposed scheme has a higher quality of recovered images and lower total node energy consumption. It is beneficial to reduce the burden of energy consumption and prolong the life of the whole network system, which has great significance for practical applications of WMSNs.

  16. Investigation of optical coherence tomography as an imaging modality in tissue engineering

    International Nuclear Information System (INIS)

    Yang Ying; Dubois, Arnaud; Qin Xiangpei; Li Jian; Haj, Alicia El; Wang, Ruikang K

    2006-01-01

    Monitoring cell profiles in 3D porous scaffolds presents a major challenge in tissue engineering. In this study, we investigate optical coherence tomography (OCT) as an imaging modality to monitor non-invasively both structures and cells in engineered tissue constructs. We employ time-domain OCT to visualize macro-structural morphology, and whole-field optical coherence microscopy to delineate the morphology of cells and constructs in a developing in vitro engineered bone tissue. The results show great potential for the use of OCT in non-invasive monitoring of cellular activities in 3D developing engineered tissues

  17. Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence

    International Nuclear Information System (INIS)

    Fukatsu, Hiroshi; Naganawa, Shinji; Yumura, Shinnichiro

    2008-01-01

    This study was aimed to validate the performance of a novel image compression method using a neural network to achieve a lossless compression. The encoding consists of the following blocks: a prediction block; a residual data calculation block; a transformation and quantization block; an organization and modification block; and an entropy encoding block. The predicted image is divided into four macro-blocks using the original image for teaching; and then redivided into sixteen sub-blocks. The predicted image is compared to the original image to create the residual image. The spatial and frequency data of the residual image are compared and transformed. Chest radiography, computed tomography (CT), magnetic resonance imaging, positron emission tomography, radioisotope mammography, ultrasonography, and digital subtraction angiography images were compressed using the AIC lossless compression method; and the compression rates were calculated. The compression rates were around 15:1 for chest radiography and mammography, 12:1 for CT, and around 6:1 for other images. This method thus enables greater lossless compression than the conventional methods. This novel method should improve the efficiency of handling of the increasing volume of medical imaging data. (author)

  18. Enhancing Perceived Quality of Compressed Images and Video with Anisotropic Diffusion and Fuzzy Filtering

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Korhonen, Jari; Forchhammer, Søren

    2013-01-01

    and subjective results on JPEG compressed images, as well as MJPEG and H.264/AVC compressed video, indicate that the proposed algorithms employing directional and spatial fuzzy filters achieve better artifact reduction than other methods. In particular, robust improvements with H.264/AVC video have been gained...

  19. SU-E-I-83: Error Analysis of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using a Preclinical Multi-Modality QA Phantom

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Y [University of Kansas Hospital, Kansas City, KS (United States); Fullerton, G; Goins, B [University of Texas Health Science Center at San Antonio, San Antonio, TX (United States)

    2015-06-15

    Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group; 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement

  20. Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

    Science.gov (United States)

    Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

    2014-03-24

    Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

  1. FogBank: a single cell segmentation across multiple cell lines and image modalities.

    Science.gov (United States)

    Chalfoun, Joe; Majurski, Michael; Dima, Alden; Stuelten, Christina; Peskin, Adele; Brady, Mary

    2014-12-30

    Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies. We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation. First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce. We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images. FogBank produces single cell segmentation from confluent cell

  2. Medical Students’ Knowledge of Indications for Imaging Modalities and Cost Analysis of Incorrect Requests, Shiraz, Iran 2011-2012

    Directory of Open Access Journals (Sweden)

    Parisa Islami Parkoohi

    2015-05-01

    Full Text Available Medical imaging has a remarkable role in the practice of clinical medicine. This study intends to evaluate the knowledge of indications of five common medical imaging modalities and estimation of the imposed cost of their non-indicated requests among medical students who attend Shiraz University of Medical Sciences, Shiraz, Iran. We conducted across-sectional survey using a self-administered questionnaire to assess the knowledge of indications of a number of medical imaging modalities among 270 medical students during their externship or internship periods. Knowledge scoring was performed according to a descriptive international grade conversion (fail to excellent using Iranian academic grading (0 to 20. In addition, we estimated the cost for incorrect selection of those modalities according to public and private tariffs in US dollars. The participation and response rate was 200/270 (74%. The mean knowledge score was fair for all modalities. Similar scores were excellent for X-ray, acceptable for Doppler ultrasonography, and fair for ultrasonography, CT scan and MRI. The total cost for non-indicated requests of those modalities equaled $104303 (public tariff and $205581 (private tariff. Medical students at Shiraz University of Medical Sciences lacked favorable knowledge about indications for common medical imaging modalities. The results of this study have shown a significant cost for non-indicated requests of medical imaging. Of note, the present radiology curriculum is in need of a major revision with regards to evidence-based radiology and health economy concerns.

  3. Medical students' knowledge of indications for imaging modalities and cost analysis of incorrect requests, shiraz, iran 2011-2012.

    Science.gov (United States)

    Islami Parkoohi, Parisa; Jalli, Reza; Danaei, Mina; Khajavian, Shiva; Askarian, Mehrdad

    2014-05-01

    Medical imaging has a remarkable role in the practice of clinical medicine. This study intends to evaluate the knowledge of indications of five common medical imaging modalities and estimation of the imposed cost of their non-indicated requests among medical students who attend Shiraz University of Medical Sciences, Shiraz, Iran. We conducted across-sectional survey using a self-administered questionnaire to assess the knowledge of indications of a number of medical imaging modalities among 270 medical students during their externship or internship periods. Knowledge scoring was performed according to a descriptive international grade conversion (fail to excellent) using Iranian academic grading (0 to 20). In addition, we estimated the cost for incorrect selection of those modalities according to public and private tariffs in US dollars. The participation and response rate was 200/270 (74%). The mean knowledge score was fair for all modalities. Similar scores were excellent for X-ray, acceptable for Doppler ultrasonography, and fair for ultrasonography, CT scan and MRI. The total cost for non-indicated requests of those modalities equaled $104303 (public tariff) and $205581 (private tariff). Medical students at Shiraz University of Medical Sciences lacked favorable knowledge about indications for common medical imaging modalities. The results of this study have shown a significant cost for non-indicated requests of medical imaging. Of note, the present radiology curriculum is in need of a major revision with regards to evidence-based radiology and health economy concerns.

  4. An compression algorithm for medical images and a display with the decoding function

    International Nuclear Information System (INIS)

    Gotoh, Toshiyuki; Nakagawa, Yukihiro; Shiohara, Morito; Yoshida, Masumi

    1990-01-01

    This paper describes and efficient image compression method for medical images, a high-speed display with the decoding function. In our method, an input image is divided into blocks, and either of Discrete Cosine Transform coding (DCT) or Block Truncation Coding (BTC) is adaptively applied on each block to improve image quality. The display, we developed, receives the compressed data from the host computer and reconstruct images of good quality at high speed using four decoding microprocessors on which our algorithm is implemented in pipeline. By the experiments, our method and display were verified to be effective. (author)

  5. PET image reconstruction with rotationally symmetric polygonal pixel grid based highly compressible system matrix

    International Nuclear Information System (INIS)

    Yu Yunhan; Xia Yan; Liu Yaqiang; Wang Shi; Ma Tianyu; Chen Jing; Hong Baoyu

    2013-01-01

    To achieve a maximum compression of system matrix in positron emission tomography (PET) image reconstruction, we proposed a polygonal image pixel division strategy in accordance with rotationally symmetric PET geometry. Geometrical definition and indexing rule for polygonal pixels were established. Image conversion from polygonal pixel structure to conventional rectangular pixel structure was implemented using a conversion matrix. A set of test images were analytically defined in polygonal pixel structure, converted to conventional rectangular pixel based images, and correctly displayed which verified the correctness of the image definition, conversion description and conversion of polygonal pixel structure. A compressed system matrix for PET image recon was generated by tap model and tested by forward-projecting three different distributions of radioactive sources to the sinogram domain and comparing them with theoretical predictions. On a practical small animal PET scanner, a compress ratio of 12.6:1 of the system matrix size was achieved with the polygonal pixel structure, comparing with the conventional rectangular pixel based tap-mode one. OS-EM iterative image reconstruction algorithms with the polygonal and conventional Cartesian pixel grid were developed. A hot rod phantom was detected and reconstructed based on these two grids with reasonable time cost. Image resolution of reconstructed images was both 1.35 mm. We conclude that it is feasible to reconstruct and display images in a polygonal image pixel structure based on a compressed system matrix in PET image reconstruction. (authors)

  6. Contributions in compression of 3D medical images and 2D images; Contributions en compression d'images medicales 3D et d'images naturelles 2D

    Energy Technology Data Exchange (ETDEWEB)

    Gaudeau, Y

    2006-12-15

    The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

  7. Photoacoustic cystography using handheld dual modal clinical ultrasound photoacoustic imaging system

    Science.gov (United States)

    Sivasubramanian, Kathyayini; Periyasamy, Vijitha; Austria, Dienzo Rhonnie; Pramanik, Manojit

    2018-02-01

    Vesicoureteral reflux is the abnormal flow of urine from your bladder back up the tubes (ureters) that connect your kidneys to your bladder. Normally, urine flows only down from your kidneys to your bladder. Vesicoureteral reflux is usually diagnosed in infants and children. The disorder increases the risk of urinary tract infections, which, if left untreated, can lead to kidney damage. X-Ray cystography is used currently to diagnose this condition which uses ionising radiation, making it harmful for patients. In this work we demonstrate the feasibility of imaging the urinary bladder using a handheld clinical ultrasound and photoacoustic dual modal imaging system in small animals (rats). Additionally, we demonstrate imaging vesicoureteral reflux using bladder mimicking phantoms. Urinary bladder imaging is done with the help of contrast agents like black ink and gold nanoparticles which have high optical absorption at 1064 nm. Imaging up to 2 cm was demonstrated with this system. Imaging was done at a framerate of 5 frames per second.

  8. Thoracic neuroblastoma: what is the best imaging modality for evaluating extent of disease?

    International Nuclear Information System (INIS)

    Slovis, T.L.; Meza, M.P.; Cushing, B.; Elkowitz, S.S.; Leonidas, J.C.; Festa, R.; Kogutt, M.S.; Fletcher, B.D.

    1997-01-01

    Thoracic neuroblastoma accounts for 15% of all cases of neuroblastoma. A minority of children with thoracic neuroblastoma will have dumbbell tumors, i.e., intraspinal extension, but only half these patients will have neurologic signs or symptoms. Hypothesis. MR imaging is the single best test to evaluate the extent of thoracic and spinal disease in thoracid neuroblastoma after the diagnosis of a mass is estbalished on plain film. A retrospective multi-institutional investigation over 7 years of all cases of thoracic neuroblastoma (n=26) imaged with CT and/or MR were reviewed for detection of the extent of disease. The chest film, nuclear bone scan, and other imaging modalities were also reviewed. The surgical and histologic correlation in each case, as well as the patients' staging and outcome, were tabulated. The chest radiography was 100% sensitive in suggesting the diagnosis. MR imaging was 100% sensitive in predicting enlarged lymph nodes, intraspinal extension, and chest wall involvement. CT was 88% sensitive for intraspinal extension but only 20% sensitive for lymph node enlargement. CT was 100% sensitive in detecting chest wall involvement. Direct comparison of CT and MR imaging in six cases revealed no difference in detection of enlarged lymph nodes or chest wall involvement. Neither test was able to detect remote disease, as noted by bone scan. The chest film is 100% sensitive in suggesting the diagnosis of thoracic neuroblastoma; MR imaging appears to be the single best test for detecting nodal involvement, intraspinal extension, and chest wall involvement. (orig.)

  9. SVD application in image and data compression - Some case studies in oceanography (Developed in MATLAB)

    Digital Repository Service at National Institute of Oceanography (India)

    Murty, T.V.R.; Rao, M.M.M.; SuryaPrakash, S.; Chandramouli, P.; Murthy, K.S.R.

    An integrated friendly-user interactive multiple Ocean Application Pacakage has been developed utilizing the well known statistical technique called Singular Value Decomposition (SVD) to achieve image and data compression in MATLAB environment...

  10. Compressive Sensing Based Bio-Inspired Shape Feature Detection CMOS Imager

    Science.gov (United States)

    Duong, Tuan A. (Inventor)

    2015-01-01

    A CMOS imager integrated circuit using compressive sensing and bio-inspired detection is presented which integrates novel functions and algorithms within a novel hardware architecture enabling efficient on-chip implementation.

  11. Role of magnetic resonance imaging in entrapment and compressive neuropathy - what, where, and how to see the peripheral nerves on the musculoskeletal magnetic resonance image: part 1. Overview and lower extremity

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sungjun [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea); Hanyang University, Kuri Hospital, Department of Diagnostic Radiology, College of Medicine, Kuri City, Kyunggi-do (Korea); Choi, Jin-Young; Huh, Yong-Min; Song, Ho-Taek; Lee, Sung-Ah [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea); Kim, Seung Min [Yonsei University, Department of Neurology, College of Medicine, Seoul (Korea); Suh, Jin-Suck [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea); Yonsei University, Research Institute of Radiological Science, College of Medicine, Seoul (Korea)

    2007-01-15

    The diagnosis of nerve entrapment and compressive neuropathy has been traditionally based on the clinical and electrodiagnostic examinations. As a result of improvements in the magnetic resonance (MR) imaging modality, it plays not only a fundamental role in the detection of space-occupying lesions but also a compensatory role in clinically and electrodiagnostically inconclusive cases. Although ultrasound has undergone further development in the past decades and shows high resolution capabilities, it has inherent limitations due to its operator dependency. We review the general concepts that should be known to evaluate the entrapment and compressive neuropathy in MR imaging. We also review the course of normal peripheral nerves, as well as various clinical demonstrations and pathological features of compressed and entrapped nerves in the lower extremities on MR imaging, according to the nerves involved. The common sites of nerve entrapment of the lower extremity are as follows: sciatic nerve around the piriformis muscle; tibial nerve at the popliteal fossa and tarsal tunnel, common peroneal nerve around the fibular neck, and digital nerve near the metatarsal head. Although MR imaging can depict the peripheral nerves in the extremities effectively, radiologists should be familiar with nerve pathways, common sites of nerve compression, and common space-occupying lesions resulting in nerve compression in MR imaging. (orig.)

  12. Role of magnetic resonance imaging in entrapment and compressive neuropathy - what, where, and how to see the peripheral nerves on the musculoskeletal magnetic resonance image: part 1. Overview and lower extremity

    International Nuclear Information System (INIS)

    Kim, Sungjun; Choi, Jin-Young; Huh, Yong-Min; Song, Ho-Taek; Lee, Sung-Ah; Kim, Seung Min; Suh, Jin-Suck

    2007-01-01

    The diagnosis of nerve entrapment and compressive neuropathy has been traditionally based on the clinical and electrodiagnostic examinations. As a result of improvements in the magnetic resonance (MR) imaging modality, it plays not only a fundamental role in the detection of space-occupying lesions but also a compensatory role in clinically and electrodiagnostically inconclusive cases. Although ultrasound has undergone further development in the past decades and shows high resolution capabilities, it has inherent limitations due to its operator dependency. We review the general concepts that should be known to evaluate the entrapment and compressive neuropathy in MR imaging. We also review the course of normal peripheral nerves, as well as various clinical demonstrations and pathological features of compressed and entrapped nerves in the lower extremities on MR imaging, according to the nerves involved. The common sites of nerve entrapment of the lower extremity are as follows: sciatic nerve around the piriformis muscle; tibial nerve at the popliteal fossa and tarsal tunnel, common peroneal nerve around the fibular neck, and digital nerve near the metatarsal head. Although MR imaging can depict the peripheral nerves in the extremities effectively, radiologists should be familiar with nerve pathways, common sites of nerve compression, and common space-occupying lesions resulting in nerve compression in MR imaging. (orig.)

  13. Emerging Cardiac Imaging Modalities for the Early Detection of Cardiotoxicity Due to Anticancer Therapies.

    Science.gov (United States)

    López-Fernández, Teresa; Thavendiranathan, Paaladinesh

    2017-06-01

    The undeniable advances in the field of oncology have finally led to a decrease in overall cancer-related mortality. However, this population of long-term cancer survivors is now facing a shift toward a substantial increase in cardiovascular morbidity and mortality. Because the development of overt cardiotoxicity can be associated with poor outcomes, preclinical identification of cardiac toxicity is important. This will promote early instauration of treatments to prevent overt heart dysfunction and allow oncologists to continue cancer therapy in an uninterrupted manner. Surveillance strategies for the early detection of cardiac injury include cardiac imaging and biomarkers during treatment. In this review, we outline existing cardiac imaging modalities to detect myocardial changes in patients undergoing cancer treatment and in survivors, and their strengths and limitations. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  14. Cardiac imaging modalities with ionizing radiation: the role of informed consent.

    Science.gov (United States)

    Paterick, Timothy E; Jan, M Fuad; Paterick, Zachary R; Tajik, A Jamil; Gerber, Thomas C

    2012-06-01

    Informed consent ideally results in patient autonomy and rational health care decisions. Frequently, patients face complex medical decisions that require a delicate balancing of anticipated benefits and potential risks, which is the concept of informed consent. This balancing process requires an understanding of available medical evidence and alternative medical options, and input from experienced physicians. The informed consent doctrine places a positive obligation on physicians to partner with patients as they try to make the best decision for their specific medical situation. The high prevalence and mortality related to heart disease in our society has led to increased cardiac imaging with modalities that use ionizing radiation. This paper reviews how physicians can meet the ideals of informed consent when considering cardiac imaging with ionizing radiation, given the limited evidence for risks and benefits. The goal is an informed patient making rational choices based on available medical information. Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  15. Endoscopic tri-modal imaging for detection of early neoplasia in Barrett's oesophagus: a multi-centre feasibility study using high-resolution endoscopy, autofluorescence imaging and narrow band imaging incorporated in one endoscopy system

    NARCIS (Netherlands)

    Curvers, W. L.; Singh, R.; Song, L.-M. Wong-Kee; Wolfsen, H. C.; Ragunath, K.; Wang, K.; Wallace, M. B.; Fockens, P.; Bergman, J. J. G. H. M.

    2008-01-01

    OBJECTIVE: To investigate the diagnostic potential of endoscopic tri-modal imaging and the relative contribution of each imaging modality (i.e. high-resolution endoscopy (HRE), autofluorescence imaging (AFI) and narrow-band imaging (NBI)) for the detection of early neoplasia in Barrett's oesophagus.

  16. Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

    Science.gov (United States)

    Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

    2018-06-01

    To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

  17. Characterization and functional correlation of multiple imaging modalities with focal choroidal excavation

    Directory of Open Access Journals (Sweden)

    Yun-Chen Chen

    2018-05-01

    Full Text Available Background: To investigate the clinical manifestations and imaging features of near-infrared autofluorescence (NIA, infrared reflectance (IR, fundus autofluorescence (FAF, indocyanine green angiography (ICGA and fluorescein angiography (FAG in the detection of patients with focal choroidal excavation (FCE identified by cross-sectional spectral-domain optical coherence tomography (SD-OCT. Methods: This retrospective cross-sectional study included 12 eyes of 10 Taiwanese patients with FCE diagnosed by SD-OCT. The areas and depths of FCE in serial cross-sectional and en-face OCT were compared in different imaging modalities. NIA, IR, FAF, ICGA and FAG images were obtained. Best corrected visual acuity, subjective distortion area in the Amsler grid and history of maculopathies were also recorded. Results: In areas where the choroid started to excavate as shown in SD-OCT, hypo-autofluorescence in NIA was noted. The area of hypo-fluorescence in NIA of all the FCE lesions showed good correlation with the size. The area of FCE was associated with complications such as choroidal neovascularization and central serous chorioretinopathy (p = 0.014, d.f = 1 and the volume (NIA area × Depth measured by SD-OCT × 1/3 was associated with subjective distortion strongly (p = 0.051, Spearman's correlation = 0.600. Conclusion: Among all image modalities, NIA was the most sensitive tool in area measurement of FCE and peripheral lesion detection. Also, the volume of FCE was associated with subjective distortion and the area was related to complications. Recording the area and volume of FCE could play an important role in monitoring complications. Keywords: Choroid-retina disease, Focal choroidal excavation, Near-infrared autofluorescence, Spectral-domain optical coherence tomography

  18. HVS scheme for DICOM image compression: Design and comparative performance evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Prabhakar, B. [Biomedical and Engineering Division, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu (India)]. E-mail: prabhakarb@iitm.ac.in; Reddy, M. Ramasubba [Biomedical and Engineering Division, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu (India)

    2007-07-15

    Advanced digital imaging technology in medical domain demands efficient and effective DICOM image compression for progressive image transmission and picture archival. Here a compression system, which incorporates sensitivities of HVS coded with SPIHT quantization, is discussed. The weighting factors derived from luminance CSF are used to transform the wavelet subband coefficients to reflect characteristics of HVS in best possible manner. Mannos et al. and Daly HVS models have been used and results are compared. To evaluate the performance, Eskicioglu chart metric is considered. Experiment is done on both Monochrome and Color Dicom images of MRI, CT, OT, and CR, natural and benchmark images. Reconstructed image through our technique showed improvement in visual quality and Eskicioglu chart metric at same compression ratios. Also the Daly HVS model based compression shows better performance perceptually and quantitatively when compared to Mannos et el. model. Further 'bior4.4' wavelet filter provides better results than 'db9' filter for this compression system. Results give strong evidence that under common boundary conditions; our technique achieves competitive visual quality, compression ratio and coding/decoding time, when compared with jpeg2000 (kakadu)

  19. Evaluation of the distortions of the digital chest image caused by the data compression

    International Nuclear Information System (INIS)

    Ando, Yutaka; Kunieda, Etsuo; Ogawa, Koichi; Tukamoto, Nobuhiro; Hashimoto, Shozo; Aoki, Makoto; Kurotani, Kenichi.

    1988-01-01

    The image data compression methods using orthogonal transforms (Discrete cosine transform, Discrete fourier transform, Hadamard transform, Haar transform, Slant transform) were analyzed. From the points of the error and the speed of the data conversion, the discrete cosine transform method (DCT) is superior to the other methods. The block quantization by the DCT for the digital chest image was used. The quality of data compressed and reconstructed images by the score analysis and the ROC curve analysis was examined. The chest image with the esophageal cancer and metastatic lung tumors was evaluated at the 17 checkpoints (the tumor, the vascular markings, the border of the heart and ribs, the mediastinal structures and et al). By our score analysis, the satisfactory ratio of the data compression is 1/5 and 1/10. The ROC analysis using normal chest images superimposed by the artificial coin lesions was made. The ROC curve of the 1/5 compressed ratio is almost as same as the original one. To summarize our study, the image data compression method using the DCT is thought to be useful for the clinical use and the 1/5 compression ratio is a tolerable ratio. (author)

  20. Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

    Science.gov (United States)

    Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

    2017-12-01

    Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

  1. Evaluation of the distortions of the digital chest image caused by the data compression

    Energy Technology Data Exchange (ETDEWEB)

    Ando, Yutaka; Kunieda, Etsuo; Ogawa, Koichi; Tukamoto, Nobuhiro; Hashimoto, Shozo; Aoki, Makoto; Kurotani, Kenichi

    1988-08-01

    The image data compression methods using orthogonal transforms (Discrete cosine transform, Discrete fourier transform, Hadamard transform, Haar transform, Slant transform) were analyzed. From the points of the error and the speed of the data conversion, the discrete cosine transform method (DCT) is superior to the other methods. The block quantization by the DCT for the digital chest image was used. The quality of data compressed and reconstructed images by the score analysis and the ROC curve analysis was examined. The chest image with the esophageal cancer and metastatic lung tumors was evaluated at the 17 checkpoints (the tumor, the vascular markings, the border of the heart and ribs, the mediastinal structures and et al). By our score analysis, the satisfactory ratio of the data compression is 1/5 and 1/10. The ROC analysis using normal chest images superimposed by the artificial coin lesions was made. The ROC curve of the 1/5 compressed ratio is almost as same as the original one. To summarize our study, the image data compression method using the DCT is thought to be useful for the clinical use and the 1/5 compression ratio is a tolerable ratio.

  2. Three-dimensional imaging of flat natural and cultural heritage objects by a Compton scattering modality

    Science.gov (United States)

    Guerrero Prado, Patricio; Nguyen, Mai K.; Dumas, Laurent; Cohen, Serge X.

    2017-01-01

    Characterization and interpretation of flat ancient material objects, such as those found in archaeology, paleoenvironments, paleontology, and cultural heritage, have remained a challenging task to perform by means of conventional x-ray tomography methods due to their anisotropic morphology and flattened geometry. To overcome the limitations of the mentioned methodologies for such samples, an imaging modality based on Compton scattering is proposed in this work. Classical x-ray tomography treats Compton scattering data as noise in the image formation process, while in Compton scattering tomography the conditions are set such that Compton data become the principal image contrasting agent. Under these conditions, we are able, first, to avoid relative rotations between the sample and the imaging setup, and second, to obtain three-dimensional data even when the object is supported by a dense material by exploiting backscattered photons. Mathematically this problem is addressed by means of a conical Radon transform and its inversion. The image formation process and object reconstruction model are presented. The feasibility of this methodology is supported by numerical simulations.

  3. Multi-modality image reconstruction for dual-head small-animal PET

    International Nuclear Information System (INIS)

    Huang, Chang-Han; Chou, Cheng-Ying

    2015-01-01

    The hybrid positron emission tomography/computed tomography (PET/CT) or positron emission tomography/magnetic resonance imaging (PET/MRI) has become routine practice in clinics. The applications of multi-modality imaging can also benefit research advances. Consequently, dedicated small-imaging system like dual-head small-animal PET (DHAPET) that possesses the advantages of high detection sensitivity and high resolution can exploit the structural information from CT or MRI. It should be noted that the special detector arrangement in DHAPET leads to severe data truncation, thereby degrading the image quality. We proposed to take advantage of anatomical priors and total variation (TV) minimization methods to reconstruct PET activity distribution form incomplete measurement data. The objective is to solve the penalized least-squares function consisted of data fidelity term, TV norm and medium root priors. In this work, we employed the splitting-based fast iterative shrinkage/thresholding algorithm to split smooth and non-smooth functions in the convex optimization problems. Our simulations studies validated that the images reconstructed by use of the proposed method can outperform those obtained by use of conventional expectation maximization algorithms or that without considering the anatomical prior information. Additionally, the convergence rate is also accelerated.

  4. Artifact reduction of compressed images and video combining adaptive fuzzy filtering and directional anisotropic diffusion

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Forchhammer, Søren; Korhonen, Jari

    2011-01-01

    and ringing artifacts, we have applied directional anisotropic diffusion. Besides that, the selection of the adaptive threshold parameter for the diffusion coefficient has also improved the performance of the algorithm. Experimental results on JPEG compressed images as well as MJPEG and H.264 compressed......Fuzzy filtering is one of the recently developed methods for reducing distortion in compressed images and video. In this paper, we combine the powerful anisotropic diffusion equations with fuzzy filtering in order to reduce the impact of artifacts. Based on the directional nature of the blocking...... videos show improvement in artifact reduction of the proposed algorithm over other directional and spatial fuzzy filters....

  5. Pleomorphic adenoma: Choice of radiographic imaging modality - Computed tomography or magnetic resonance imaging? Illustration through a case report

    Directory of Open Access Journals (Sweden)

    Shalu Rai

    2013-01-01

    Full Text Available Introduction: Pleomorphic adenoma (PA is the most common benign neoplasm of the major salivary glands arising primarily from the parotid gland. Computed tomography (CT is one of the primary imaging modalities used to assess the tumors of salivary glands. However, magnetic resonance imaging (MRI may provide additional information over CT. Case Report: We report the case of a 60-year-old male with a slowly enlarging, well-defined, round, painless, non-fixated, rubber-like swelling over the left ramus region below the ear, measuring about 4 × 4.5 cm, covering the lower border of the mandible near the angle. A provisional diagnosis of PA was given and CT and MRI were used to study the lesion. Discussion: Through this case, which was suspected to have undergone malignant transformation because of indistinct margins and focal hypodense areas on CT but was later confirmed to be a benign salivary gland tumor on MRI, we illustrate the role of CT and MRI as diagnostic aids in PA and emphasize on what should be the choice of imaging modality for parotid tumors.

  6. Color image lossy compression based on blind evaluation and prediction of noise characteristics

    Science.gov (United States)

    Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Egiazarian, Karen O.; Lepisto, Leena

    2011-03-01

    The paper deals with JPEG adaptive lossy compression of color images formed by digital cameras. Adaptation to noise characteristics and blur estimated for each given image is carried out. The dominant factor degrading image quality is determined in a blind manner. Characteristics of this dominant factor are then estimated. Finally, a scaling factor that determines quantization steps for default JPEG table is adaptively set (selected). Within this general framework, two possible strategies are considered. A first one presumes blind estimation for an image after all operations in digital image processing chain just before compressing a given raster image. A second strategy is based on prediction of noise and blur parameters from analysis of RAW image under quite general assumptions concerning characteristics parameters of transformations an image will be subject to at further processing stages. The advantages of both strategies are discussed. The first strategy provides more accurate estimation and larger benefit in image compression ratio (CR) compared to super-high quality (SHQ) mode. However, it is more complicated and requires more resources. The second strategy is simpler but less beneficial. The proposed approaches are tested for quite many real life color images acquired by digital cameras and shown to provide more than two time increase of average CR compared to SHQ mode without introducing visible distortions with respect to SHQ compressed images.

  7. Observer detection of image degradation caused by irreversible data compression processes

    Science.gov (United States)

    Chen, Ji; Flynn, Michael J.; Gross, Barry; Spizarny, David

    1991-05-01

    Irreversible data compression methods have been proposed to reduce the data storage and communication requirements of digital imaging systems. In general, the error produced by compression increases as an algorithm''s compression ratio is increased. We have studied the relationship between compression ratios and the detection of induced error using radiologic observers. The nature of the errors was characterized by calculating the power spectrum of the difference image. In contrast with studies designed to test whether detected errors alter diagnostic decisions, this study was designed to test whether observers could detect the induced error. A paired-film observer study was designed to test whether induced errors were detected. The study was conducted with chest radiographs selected and ranked for subtle evidence of interstitial disease, pulmonary nodules, or pneumothoraces. Images were digitized at 86 microns (4K X 5K) and 2K X 2K regions were extracted. A full-frame discrete cosine transform method was used to compress images at ratios varying between 6:1 and 60:1. The decompressed images were reprinted next to the original images in a randomized order with a laser film printer. The use of a film digitizer and a film printer which can reproduce all of the contrast and detail in the original radiograph makes the results of this study insensitive to instrument performance and primarily dependent on radiographic image quality. The results of this study define conditions for which errors associated with irreversible compression cannot be detected by radiologic observers. The results indicate that an observer can detect the errors introduced by this compression algorithm for compression ratios of 10:1 (1.2 bits/pixel) or higher.

  8. Magnetic resonance imaging of vascular compression in trigeminal neuralgia and hemifacial spasms

    International Nuclear Information System (INIS)

    Nagaseki, Yoshishige; Horikoshi, Tohru; Omata, Tomohiro; Sugita, Masao; Nukui, Hideaki; Sakamoto, Hajime; Kumagai, Hiroshi; Sasaki, Hideo; Tsuji, Reizou.

    1991-01-01

    We show how neurosurgical planning can benefit from the better visualization of the precise vascular compression of the nerve provided by the oblique-sagittal and gradient-echo method (OS-GR image) using magnetic resonance images (MRI). The scans of 3 patients with trigeminal neuralgia (TN) and of 15 with hemifacial spasm (HFS) were analyzed for the presence and appearance of the vascular compression of the nerves. Imaging sequences consisted of an OS-GR image (TR/TE: 200/20, 3-mm-thick slice) cut along each nerve shown by the axial view, which was scanned at the angle of 105 degrees taken between the dorsal line of the brain stem and the line corresponding to the pontomedullary junction. In the OS-GR images of the TN's, the vascular compressions of the root entry zone (REZ) of the trigeminal nerve were well visualized as high-intensity lines in the 2 cases whose vessels were confirmed intraoperatively. In the other case, with atypical facial pain, vascular compression was confirmed at the rostral distal site on the fifth nerve, apart from the REZ. In the 15 cases of HFS, twelve OS-GR images (80%) demonstrated vascular compressions at the REZ of the facial nerves from the direction of the caudoventral side. During the surgery for these 12 cases, in 11 cases (excepting the 1 case whose facial nerve was not compressed by any vessels), vascular compressions were confirmed corresponding to the findings of the OS-GR images. Among the 10 OS-GR images on the non-affected side, two false-positive findings were visualized. It is concluded that OS-GR images obtained by means of MRI may serve as a useful planning aid prior to microvascular decompression for cases of TN and HFS. (author)

  9. Characterization of Diesel and Gasoline Compression Ignition Combustion in a Rapid Compression-Expansion Machine using OH* Chemiluminescence Imaging

    Science.gov (United States)

    Krishnan, Sundar Rajan; Srinivasan, Kalyan Kumar; Stegmeir, Matthew

    2015-11-01

    Direct-injection compression ignition combustion of diesel and gasoline were studied in a rapid compression-expansion machine (RCEM) using high-speed OH* chemiluminescence imaging. The RCEM (bore = 84 mm, stroke = 110-250 mm) was used to simulate engine-like operating conditions at the start of fuel injection. The fuels were supplied by a high-pressure fuel cart with an air-over-fuel pressure amplification system capable of providing fuel injection pressures up to 2000 bar. A production diesel fuel injector was modified to provide a single fuel spray for both diesel and gasoline operation. Time-resolved combustion pressure in the RCEM was measured using a Kistler piezoelectric pressure transducer mounted on the cylinder head and the instantaneous piston displacement was measured using an inductive linear displacement sensor (0.05 mm resolution). Time-resolved, line-of-sight OH* chemiluminescence images were obtained using a Phantom V611 CMOS camera (20.9 kHz @ 512 x 512 pixel resolution, ~ 48 μs time resolution) coupled with a short wave pass filter (cut-off ~ 348 nm). The instantaneous OH* distributions, which indicate high temperature flame regions within the combustion chamber, were used to discern the characteristic differences between diesel and gasoline compression ignition combustion. The authors gratefully acknowledge facilities support for the present work from the Energy Institute at Mississippi State University.

  10. ITERATION FREE FRACTAL COMPRESSION USING GENETIC ALGORITHM FOR STILL COLOUR IMAGES

    Directory of Open Access Journals (Sweden)

    A.R. Nadira Banu Kamal

    2014-02-01

    Full Text Available The storage requirements for images can be excessive, if true color and a high-perceived image quality are desired. An RGB image may be viewed as a stack of three gray-scale images that when fed into the red, green and blue inputs of a color monitor, produce a color image on the screen. The abnormal size of many images leads to long, costly, transmission times. Hence, an iteration free fractal algorithm is proposed in this research paper to design an efficient search of the domain pools for colour image compression using Genetic Algorithm (GA. The proposed methodology reduces the coding process time and intensive computation tasks. Parameters such as image quality, compression ratio and coding time are analyzed. It is observed that the proposed method achieves excellent performance in image quality with reduction in storage space.

  11. Low-complexity Compression of High Dynamic Range Infrared Images with JPEG compatibility

    DEFF Research Database (Denmark)

    Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

    2017-01-01

    data size, then we include the raw residual image instead. If the residual image contains only zero values or the quality factor for it is 0 then we do not include the residual image into the header. Experimental results show that compared with JPEG-XT Part 6 with ’global Reinhard’ tone-mapping....... Then we compress each image by a JPEG baseline encoder and include the residual image bit stream into the application part of JPEG header of the base image. As a result, the base image can be reconstructed by JPEG baseline decoder. If the JPEG bit stream size of the residual image is higher than the raw...

  12. Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

    Directory of Open Access Journals (Sweden)

    Jin Li

    2014-01-01

    Full Text Available Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC combined with image data compression (IDC approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE. Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS-based algorithm has better compression performance than the traditional compression approaches.

  13. Multispectral image compression based on DSC combined with CCSDS-IDC.

    Science.gov (United States)

    Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

    2014-01-01

    Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

  14. Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

    Science.gov (United States)

    Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2018-01-01

    A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

  15. Facile Fabrication of Animal-Specific Positioning Molds For Multi-modality Molecular Imaging

    International Nuclear Information System (INIS)

    Park, Jeong Chan; Oh, Ji Eun; Woo, Seung Tae

    2008-01-01

    Recently multi-modal imaging system has become widely adopted in molecular imaging. We tried to fabricate animal-specific positioning molds for PET/MR fusion imaging using easily available molding clay and rapid foam. The animal-specific positioning molds provide immobilization and reproducible positioning of small animal. Herein, we have compared fiber-based molding clay with rapid foam in fabricating the molds of experimental animal. The round bottomed-acrylic frame, which fitted into microPET gantry, was prepared at first. The experimental mice was anesthetized and placed on the mold for positioning. Rapid foam and fiber-based clay were used to fabricate the mold. In case of both rapid foam and the clay, the experimental animal needs to be pushed down smoothly into the mold for positioning. However, after the mouse was removed, the fabricated clay needed to be dried completely at 60 .deg. C in oven overnight for hardening. Four sealed pipe tips containing [ 18 F]FDG solution were used as fiduciary markers. After injection of [ 18 F]FDG via tail vein, microPET scanning was performed. Successively, MRI scanning was followed in the same animal. Animal-specific positioning molds were fabricated using rapid foam and fiber-based molding clay for multimodality imaging. Functional and anatomical images were obtained with microPET and MRI, respectively. The fused PET/MR images were obtained using freely available AMIDE program. Animal-specific molds were successfully prepared using easily available rapid foam, molding clay and disposable pipet tips. Thanks to animal-specific molds, fusion images of PET and MR were co-registered with negligible misalignment

  16. 3D reconstruction of microvascular flow phantoms with hybrid imaging modalities

    Science.gov (United States)

    Lin, Jingying; Hsiung, Kevin; Ritenour, Russell; Golzarian, Jafar

    2011-03-01

    Microvascular flow phantoms were built to aid the development of a hemodynamic simulation model for treating hepatocelluar carcinoma. The goal is to predict the blood flow routing for embolotherapy planning. Embolization is to deliver agents (e.g. microspheres) to the vicinity of the tumor to obstruct blood supply and nutrients to the tumor, targeting into 30 - 40 μm arterioles. Due to the size of the catheter, it has to release microspheres at an upper stream location, which may not localize the blocking effect. Accurate anatomical descriptions of microvasculature will help to conduct a reliable simulation and prepare a successful embolization strategy. Modern imaging devices can generate 3D reconstructions with ease. However, with a fixed detector size, larger field of view yields lower resolution. Clinical CT images can't be used to measure micro vessel dimensions, while micro-CT requires more acquisitions to reconstruct larger vessels. A multi-tiered, montage 3D reconstruction method with hybrid-modality imagery is devised to minimize the reconstruction effort. Regular CT is used for larger vessels and micro-CT is used for micro vessels. The montage approach aims to stitch up images with different resolutions and orientations. A resolution-adaptable 3D image registration is developed to assemble the images. We have created vessel phantoms that consist of several tiers of bifurcating polymer tubes in reducing diameters, down to 25 μm. No previous work of physical flow phantom has ventured into this small scale. Overlapping phantom images acquired from clinical CT and micro-CT are used to verify the image registration fidelity.

  17. Informational analysis for compressive sampling in radar imaging.

    Science.gov (United States)

    Zhang, Jingxiong; Yang, Ke

    2015-03-24

    Compressive sampling or compressed sensing (CS) works on the assumption of the sparsity or compressibility of the underlying signal, relies on the trans-informational capability of the measurement matrix employed and the resultant measurements, operates with optimization-based algorithms for signal reconstruction and is thus able to complete data compression, while acquiring data, leading to sub-Nyquist sampling strategies that promote efficiency in data acquisition, while ensuring certain accuracy criteria. Information theory provides a framework complementary to classic CS theory for analyzing information mechanisms and for determining the necessary number of measurements in a CS environment, such as CS-radar, a radar sensor conceptualized or designed with CS principles and techniques. Despite increasing awareness of information-theoretic perspectives on CS-radar, reported research has been rare. This paper seeks to bridge the gap in the interdisciplinary area of CS, radar and information theory by analyzing information flows in CS-radar from sparse scenes to measurements and determining sub-Nyquist sampling rates necessary for scene reconstruction within certain distortion thresholds, given differing scene sparsity and average per-sample signal-to-noise ratios (SNRs). Simulated studies were performed to complement and validate the information-theoretic analysis. The combined strategy proposed in this paper is valuable for information-theoretic orientated CS-radar system analysis and performance evaluation.

  18. The guarantee of the consistency of patient information through modality worklist among PACS, RIS and imaging equipments

    International Nuclear Information System (INIS)

    Luo Min; Peng Chenglin; Wang Xiaolin; Luo Song; Lei Wenyong; Wang Kang; Wang Xuejian; Wen Hongyu; Wu Hongxing

    2003-01-01

    Objective: To realize the consistency of patient information through modality worklist among picture archiving and communication system (PACS), radiology information systems (RIS), and imaging equipments. Methods: Many digital modalities including GE Signa 1.5 T MR system, digital mammography, Agfa digital radiography, computed radiography, GE CT, and etc were installed in our hospital. Since the GE PACS system was in English version, the images were saved and the information was managed to PACS without a truly worklist. Two months later, while still using the previous PACS, the consistency of patient information was resolved through modality worklist by adopting the international advanced approach to realize thread worklist of digital imaging and communication in medicine. The information in Chinese will be transformed into information in English in RIS system and saved as the English information to worklist. Results: After the implementation and integration of PACS and RIS was achieved in my hospital, the consistency of patient information was guaranteed through modality worklist between RIS and imaging equipments and the first-rate effect was acquired. The patient information could be checked, edited, and created by using the Chinese RIS system on all diagnostic workstations. Conclusion: The consistency of patient information through modality worklist was realized among PACS, RIS, and imaging equipments, yet at present, the question of guarantee the consistency of patient information must be thought over in PACS building

  19. An introduction to video image compression and authentication technology for safeguards applications

    International Nuclear Information System (INIS)

    Johnson, C.S.

    1995-01-01

    Verification of a video image has been a major problem for safeguards for several years. Various verification schemes have been tried on analog video signals ever since the mid-1970's. These schemes have provided a measure of protection but have never been widely adopted. The development of reasonably priced complex video processing integrated circuits makes it possible to digitize a video image and then compress the resulting digital file into a smaller file without noticeable loss of resolution. Authentication and/or encryption algorithms can be more easily applied to digital video files that have been compressed. The compressed video files require less time for algorithm processing and image transmission. An important safeguards application for authenticated, compressed, digital video images is in unattended video surveillance systems and remote monitoring systems. The use of digital images in the surveillance system makes it possible to develop remote monitoring systems that send images over narrow bandwidth channels such as the common telephone line. This paper discusses the video compression process, authentication algorithm, and data format selected to transmit and store the authenticated images

  20. Evaluation of 3D modality-independent elastography for breast imaging: a simulation study

    International Nuclear Information System (INIS)

    Ou, J J; Ong, R E; Yankeelov, T E; Miga, M I

    2008-01-01

    This paper reports on the development and preliminary testing of a three-dimensional implementation of an inverse problem technique for extracting soft-tissue elasticity information via non-rigid model-based image registration. The modality-independent elastography (MIE) algorithm adjusts the elastic properties of a biomechanical model to achieve maximal similarity between images acquired under different states of static loading. A series of simulation experiments with clinical image sets of human breasts were performed to test the ability of the method to identify and characterize a radiographically occult stiff lesion. Because boundary conditions are a critical input to the algorithm, a comparison of three methods for semi-automated surface point correspondence was conducted in the context of systematic and randomized noise processes. The results illustrate that 3D MIE was able to successfully reconstruct elasticity images using data obtained from both magnetic resonance and x-ray computed tomography systems. The lesion was localized correctly in all cases and its relative elasticity found to be reasonably close to the true values (3.5% with the use of spatial priors and 11.6% without). In addition, the inaccuracies of surface registration performed with thin-plate spline interpolation did not exceed empiric thresholds of unacceptable boundary condition error

  1. Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

    Science.gov (United States)

    Fuerst, Bernhard; Tateno, Keisuke; Johnson, Alex; Fotouhi, Javad; Osgood, Greg; Tombari, Federico; Navab, Nassir

    2017-01-01

    Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red–green–blue–depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion. PMID:29184659

  2. Parallelization of one image compression method. Wavelet, Transform, Vector Quantization and Huffman Coding

    International Nuclear Information System (INIS)

    Moravie, Philippe

    1997-01-01

    Today, in the digitized satellite image domain, the needs for high dimension increase considerably. To transmit or to stock such images (more than 6000 by 6000 pixels), we need to reduce their data volume and so we have to use real-time image compression techniques. The large amount of computations required by image compression algorithms prohibits the use of common sequential processors, for the benefits of parallel computers. The study presented here deals with parallelization of a very efficient image compression scheme, based on three techniques: Wavelets Transform (WT), Vector Quantization (VQ) and Entropic Coding (EC). First, we studied and implemented the parallelism of each algorithm, in order to determine the architectural characteristics needed for real-time image compression. Then, we defined eight parallel architectures: 3 for Mallat algorithm (WT), 3 for Tree-Structured Vector Quantization (VQ) and 2 for Huffman Coding (EC). As our system has to be multi-purpose, we chose 3 global architectures between all of the 3x3x2 systems available. Because, for technological reasons, real-time is not reached at anytime (for all the compression parameter combinations), we also defined and evaluated two algorithmic optimizations: fix point precision and merging entropic coding in vector quantization. As a result, we defined a new multi-purpose multi-SMIMD parallel machine, able to compress digitized satellite image in real-time. The definition of the best suited architecture for real-time image compression was answered by presenting 3 parallel machines among which one multi-purpose, embedded and which might be used for other applications on board. (author) [fr

  3. A multi-modality concept for radiotherapy planning with imaging techniques

    International Nuclear Information System (INIS)

    Schultze, J.

    1993-01-01

    The reported multi-modality concept of radiotherapy planning in the LAN can be realised in any hospital with standard equipment, although in some cases by way of auxiliary configurations. A software is currently developed as a tool for reducing the entire planning work. The heart of any radiotherapy planning is the therapy simulator, which has to be abreast with the requirements of modern radiotherapy. Integration of tomograpy, digitalisation, and electronic data processing has added important modalities to therapy planning which allow more precise target volume definition, and better biophysical planning. This is what is needed in order to achieve well differentiated radiotherapy for treatment of the manifold tumors, and the quality standards expected by the supervisory quality assurance regime and the population. At present, the CT data still are transferred indirect, on storage media, to the EDP processing system of the radiotherapy planning system. Based on the tomographic slices given by the imaging data, the contours and technical problem solutions are derived automatically, either for multi-field radiotherapy or moving field irradiation, depending on the anatomy or the targets to be protected from ionizing radiation. (orig./VHE) [de

  4. A convergent functional architecture of the insula emerges across imaging modalities.

    Science.gov (United States)

    Kelly, Clare; Toro, Roberto; Di Martino, Adriana; Cox, Christine L; Bellec, Pierre; Castellanos, F Xavier; Milham, Michael P

    2012-07-16

    Empirical evidence increasingly supports the hypothesis that patterns of intrinsic functional connectivity (iFC) are sculpted by a history of evoked coactivation within distinct neuronal networks. This, together with evidence of strong correspondence among the networks defined by iFC and those delineated using a variety of other neuroimaging techniques, suggests a fundamental brain architecture detectable across multiple functional and structural imaging modalities. Here, we leverage this insight to examine the functional organization of the human insula. We parcellated the insula on the basis of three distinct neuroimaging modalities - task-evoked coactivation, intrinsic (i.e., task-independent) functional connectivity, and gray matter structural covariance. Clustering of these three different covariance-based measures revealed a convergent elemental organization of the insula that likely reflects a fundamental brain architecture governing both brain structure and function at multiple spatial scales. While not constrained to be hierarchical, our parcellation revealed a pseudo-hierarchical, multiscale organization that was consistent with previous clustering and meta-analytic studies of the insula. Finally, meta-analytic examination of the cognitive and behavioral domains associated with each of the insular clusters obtained elucidated the broad functional dissociations likely underlying the topography observed. To facilitate future investigations of insula function across healthy and pathological states, the insular parcels have been made freely available for download via http://fcon_1000.projects.nitrc.org, along with the analytic scripts used to perform the parcellations. Copyright © 2012 Elsevier Inc. All rights reserved.

  5. An analytical look at the effects of compression on medical images

    OpenAIRE

    Persons, Kenneth; Palisson, Patrice; Manduca, Armando; Erickson, Bradley J.; Savcenko, Vladimir

    1997-01-01

    This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for...

  6. Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager

    Science.gov (United States)

    Keymeulen, Didlier; Aranki, Nazeeh I.; Klimesh, Matthew A.; Bakhshi, Alireza

    2012-01-01

    Efficient onboard data compression can reduce the data volume from hyperspectral imagers on NASA and DoD spacecraft in order to return as much imagery as possible through constrained downlink channels. Lossless compression is important for signature extraction, object recognition, and feature classification capabilities. To provide onboard data compression, a hardware implementation of a lossless hyperspectral compression algorithm was developed using a field programmable gate array (FPGA). The underlying algorithm is the Fast Lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral- Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), p. 26 with the modification reported in Lossless, Multi-Spectral Data Comressor for Improved Compression for Pushbroom-Type Instruments (NPO-45473), NASA Tech Briefs, Vol. 32, No. 7 (July 2008) p. 63, which provides improved compression performance for data from pushbroom-type imagers. An FPGA implementation of the unmodified FL algorithm was previously developed and reported in Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System (NPO-46867), NASA Tech Briefs, Vol. 36, No. 5 (May 2012) p. 42. The essence of the FL algorithm is adaptive linear predictive compression using the sign algorithm for filter adaption. The FL compressor achieves a combination of low complexity and compression effectiveness that exceeds that of stateof- the-art techniques currently in use. The modification changes the predictor structure to tolerate differences in sensitivity of different detector elements, as occurs in pushbroom-type imagers, which are suitable for spacecraft use. The FPGA implementation offers a low-cost, flexible solution compared to traditional ASIC (application specific integrated circuit) and can be integrated as an intellectual property (IP) for part of, e.g., a design that manages the instrument interface. The FPGA implementation was benchmarked on the Xilinx

  7. System Characterizations and Optimized Reconstruction Methods for Novel X-ray Imaging Modalities

    Science.gov (United States)

    Guan, Huifeng

    In the past decade there have been many new emerging X-ray based imaging technologies developed for different diagnostic purposes or imaging tasks. However, there exist one or more specific problems that prevent them from being effectively or efficiently employed. In this dissertation, four different novel X-ray based imaging technologies are discussed, including propagation-based phase-contrast (PB-XPC) tomosynthesis, differential X-ray phase-contrast tomography (D-XPCT), projection-based dual-energy computed radiography (DECR), and tetrahedron beam computed tomography (TBCT). System characteristics are analyzed or optimized reconstruction methods are proposed for these imaging modalities. In the first part, we investigated the unique properties of propagation-based phase-contrast imaging technique when combined with the X-ray tomosynthesis. Fourier slice theorem implies that the high frequency components collected in the tomosynthesis data can be more reliably reconstructed. It is observed that the fringes or boundary enhancement introduced by the phase-contrast effects can serve as an accurate indicator of the true depth position in the tomosynthesis in-plane image. In the second part, we derived a sub-space framework to reconstruct images from few-view D-XPCT data set. By introducing a proper mask, the high frequency contents of the image can be theoretically preserved in a certain region of interest. A two-step reconstruction strategy is developed to mitigate the risk of subtle structures being oversmoothed when the commonly used total-variation regularization is employed in the conventional iterative framework. In the thirt part, we proposed a practical method to improve the quantitative accuracy of the projection-based dual-energy material decomposition. It is demonstrated that applying a total-projection-length constraint along with the dual-energy measurements can achieve a stabilized numerical solution of the decomposition problem, thus overcoming the

  8. Antibiofouling polymer coated gold nanoparticles as a dual modal contrast agent for X-ray and photoacoustic imaging

    International Nuclear Information System (INIS)

    Guojia Huang; Yi Yuan; Xing Da

    2011-01-01

    X-ray is one of the most useful diagnostic tools in hospitals in terms of frequency of use and cost, while photoacoustic (PA) imaging is a rapidly emerging non-invasive imaging technology that integrates the merits of high optical contrast with high ultrasound resolution. In this study, for the first time, we used gold nanoparticles (GNPs) as a dual modal contrast agent for X-ray and PA imaging. Soft gelatin phantoms with embedded tumor simulators of GNPs in various concentrations are clearly shown in both X-ray and PA imaging. With GNPs as a dual modal contrast agent, X-ray can fast detect the position of tumor and provide morphological information, whereas PA imaging has important potential applications in the image guided therapy of superficial tumors such as breast cancer, melanoma and Merkel cell carcinoma.

  9. Dual-Modal Nanoprobes for Imaging of Mesenchymal Stem Cell Transplant by MRI and Fluorescence Imaging

    International Nuclear Information System (INIS)

    Sung, Chang Kyu; Hong, Kyung Ah; Lin, Shun Mei

    2009-01-01

    To determine the feasibility of labeling human mesenchymal stem cells (hMSCs) with bifunctional nanoparticles and assessing their potential as imaging probes in the monitoring of hMSC transplantation. The T1 and T2 relaxivities of the nanoparticles (MNP SiO 2 [RITC]-PEG) were measured at 1.5T and 3T magnetic resonance scanner. Using hMSCs and the nanoparticles, labeling efficiency, toxicity, and proliferation were assessed. Confocal laser scanning microscopy and transmission electron microscopy were used to specify the intracellular localization of the endocytosed iron nanoparticles. We also observed in vitro and in vivo visualization of the labeled hMSCs with a 3T MR scanner and optical imaging. MNP SiO 2 (RITC)-PEG showed both superparamagnetic and fluorescent properties. The r 1 and r 2 relaxivity values of the MNP SiO 2 (RITC)-PEG were 0.33 and 398 mM -1 s -1 at 1.5T, respectively, and 0.29 and 453 mM -1 s -1 at 3T, respectively. The effective internalization of MNP SiO 2 (RITC)-PEG into hMSCs was observed by confocal laser scanning fluorescence microscopy. The transmission electron microscopy images showed that MNP SiO 2 (RITC)-PEG was internalized into the cells and mainly resided in the cytoplasm. The viability and proliferation of MNP SiO 2 (RITC)-PEG-labeled hMSCs were not significantly different from the control cells. MNP SiO 2 (RITC)-PEG-labeled hMSCs were observed in vitro and in vivo with optical and MR imaging. MNP SiO 2 (RITC)-PEG can be a useful contrast agent for stem cell imaging, which is suitable for a bimodal detection by MRI and optical imaging

  10. Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

    Directory of Open Access Journals (Sweden)

    Siming Bayer

    2017-01-01

    Full Text Available Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF, and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work.

  11. USING H.264/AVC-INTRA FOR DCT BASED SEGMENTATION DRIVEN COMPOUND IMAGE COMPRESSION

    Directory of Open Access Journals (Sweden)

    S. Ebenezer Juliet

    2011-08-01

    Full Text Available This paper presents a one pass block classification algorithm for efficient coding of compound images which consists of multimedia elements like text, graphics and natural images. The objective is to minimize the loss of visual quality of text during compression by separating text information which needs high special resolution than the pictures and background. It segments computer screen images into text/graphics and picture/background classes based on DCT energy in each 4x4 block, and then compresses both text/graphics pixels and picture/background blocks by H.264/AVC with variable quantization parameter. Experimental results show that the single H.264/AVC-INTRA coder with variable quantization outperforms single coders such as JPEG, JPEG-2000 for compound images. Also the proposed method improves the PSNR value significantly than standard JPEG, JPEG-2000 and while keeping competitive compression ratios.

  12. Inter frame motion estimation and its application to image sequence compression: an introduction

    International Nuclear Information System (INIS)

    Cremy, C.

    1996-01-01

    With the constant development of new communication technologies like, digital TV, teleconference, and the development of image analysis applications, there is a growing volume of data to manage. Compression techniques are required for the transmission and storage of these data. Dealing with original images would require the use of expansive high bandwidth communication devices and huge storage media. Image sequence compression can be achieved by means of interframe estimation that consists in retrieving redundant information relative to zones where there is little motion between two frames. This paper is an introduction to some motion estimation techniques like gradient techniques, pel-recursive, block-matching, and its application to image sequence compression. (Author) 17 refs

  13. Differential diagnosis of benign and malignant vertebral compression fractures with MR imaging

    International Nuclear Information System (INIS)

    Staebler, A.; Krimmel, K.; Seiderer, M.; Gaertner, C.; Fritsch, S.; Raum, W.

    1992-01-01

    42 patients with known malignancy and vertebral compressions underwent MRI. Sagittal T 1 -weighted spin-echo images pre and post Gd-DTPA, out of phase long TR gradient-echo images (GE) and short T 1 inversion recovery images (STIR) were obtained at 1.0 T. In 39 of 42 cases a correct differentiation between osteoporotic and tumorous vertebral compression fractures was possible by quantification and correlation of SE and GE signal intensities. Gd-DTPA did not improve differential diagnosis, since both tumour infiltration and bone marrow oedema in acute compression fracture showed comparable enhancement. STIR-sequences were most sensitive for pathology but unspecific due to a comparable amount of water in tumour tissue and bone marrow oedema. Susceptibility-induced signal reduction in GE images and morphologic criteria proved to be most reliable for differentiation of benign and tumour-related fractures. (orig./GDG) [de

  14. Adaptive Binary Arithmetic Coder-Based Image Feature and Segmentation in the Compressed Domain

    Directory of Open Access Journals (Sweden)

    Hsi-Chin Hsin

    2012-01-01

    Full Text Available Image compression is necessary in various applications, especially for efficient transmission over a band-limited channel. It is thus desirable to be able to segment an image in the compressed domain directly such that the burden of decompressing computation can be avoided. Motivated by the adaptive binary arithmetic coder (MQ coder of JPEG2000, we propose an efficient scheme to segment the feature vectors that are extracted from the code stream of an image. We modify the Compression-based Texture Merging (CTM algorithm to alleviate the influence of overmerging problem by making use of the rate distortion information. Experimental results show that the MQ coder-based image segmentation is preferable in terms of the boundary displacement error (BDE measure. It has the advantage of saving computational cost as the segmentation results even at low rates of bits per pixel (bpp are satisfactory.

  15. Adaptive bit plane quadtree-based block truncation coding for image compression

    Science.gov (United States)

    Li, Shenda; Wang, Jin; Zhu, Qing

    2018-04-01

    Block truncation coding (BTC) is a fast image compression technique applied in spatial domain. Traditional BTC and its variants mainly focus on reducing computational complexity for low bit rate compression, at the cost of lower quality of decoded images, especially for images with rich texture. To solve this problem, in this paper, a quadtree-based block truncation coding algorithm combined with adaptive bit plane transmission is proposed. First, the direction of edge in each block is detected using Sobel operator. For the block with minimal size, adaptive bit plane is utilized to optimize the BTC, which depends on its MSE loss encoded by absolute moment block truncation coding (AMBTC). Extensive experimental results show that our method gains 0.85 dB PSNR on average compare to some other state-of-the-art BTC variants. So it is desirable for real time image compression applications.

  16. NIR hyperspectral compressive imager based on a modified Fabry–Perot resonator

    Science.gov (United States)

    Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Stern, Adrian

    2018-04-01

    The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonator spectroscopy technique. Within the framework of CS, and by using a modified Fabry–Perot resonator, a sequence of spectrally modulated images is used to recover NIR HS datacubes. Owing to the innovative CS design, we demonstrate the ability to reconstruct NIR HS images with hundreds of spectral bands from an order of magnitude fewer measurements, i.e. with a compression ratio of about 10:1. This high compression ratio, together with the high optical throughput of the system, facilitates fast acquisition of large HS datacubes.

  17. Context-dependent JPEG backward-compatible high-dynamic range image compression

    Science.gov (United States)

    Korshunov, Pavel; Ebrahimi, Touradj

    2013-10-01

    High-dynamic range (HDR) imaging is expected, together with ultrahigh definition and high-frame rate video, to become a technology that may change photo, TV, and film industries. Many cameras and displays capable of capturing and rendering both HDR images and video are already available in the market. The popularity and full-public adoption of HDR content is, however, hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of low-dynamic range (LDR) displays that are unable to render HDR. To facilitate the wide spread of HDR usage, the backward compatibility of HDR with commonly used legacy technologies for storage, rendering, and compression of video and images are necessary. Although many tone-mapping algorithms are developed for generating viewable LDR content from HDR, there is no consensus of which algorithm to use and under which conditions. We, via a series of subjective evaluations, demonstrate the dependency of the perceptual quality of the tone-mapped LDR images on the context: environmental factors, display parameters, and image content itself. Based on the results of subjective tests, it proposes to extend JPEG file format, the most popular image format, in a backward compatible manner to deal with HDR images also. An architecture to achieve such backward compatibility with JPEG is proposed. A simple implementation of lossy compression demonstrates the efficiency of the proposed architecture compared with the state-of-the-art HDR image compression.

  18. Multiview Depth-Image Compression Using an Extended H.264 Encoder

    NARCIS (Netherlands)

    Morvan, Y.; Farin, D.S.; With, de P.H.N.; Blanc-Talon, J.; Philips, W.

    2007-01-01

    This paper presents a predictive-coding algorithm for the compression of multiple depth-sequences obtained from a multi-camera acquisition setup. The proposed depth-prediction algorithm works by synthesizing a virtual depth-image that matches the depth-image (of the predicted camera). To generate

  19. Edge-based compression of cartoon-like images with homogeneous diffusion

    DEFF Research Database (Denmark)

    Mainberger, Markus; Bruhn, Andrés; Weickert, Joachim

    2011-01-01

    Edges provide semantically important image features. In this paper a lossy compression method for cartoon-like images is presented, which is based on edge information. Edges together with some adjacent grey/colour values are extracted and encoded using a classical edge detector, binary compressio...

  20. Comparing subjective and objective quality assessment of HDR images compressed with JPEG-XT

    DEFF Research Database (Denmark)

    Mantel, Claire; Ferchiu, Stefan Catalin; Forchhammer, Søren

    2014-01-01

    In this paper a subjective test in which participants evaluate the quality of JPEG-XT compressed HDR images is presented. Results show that for the selected test images and display, the subjective quality reached its saturation point starting around 3bpp. Objective evaluations are obtained...

  1. Establishing physical criteria to stop the losing compression of digital medical imaging

    International Nuclear Information System (INIS)

    Perez Diaz, M

    2008-01-01

    Full text: A key to store and/or transmit digital medical images obtained from modern technologies is the size in bytes they occupy difficulty. One way to solve the above is the implementation of compression algorithms (codecs) with or without losses. Particularly the latter do allow significant reductions in the size of the images, but if not applied on solid scientific criteria can lead to useful diagnostic information is lost. This talk takes a description and assessment of the quality of image obtained after the application of current compression codecs from analysis of physical parameters such as: Spatial resolution, random noise , contrast and image generation devices. Open for Medical Physics and Image Processing, directed toward establishing objective criteria to stop losing compression, based on the implementation of Univariate and bivariate traditional metrics such as mean square error introduced by each issue focuses rate compression, Signal to Noise peak to peak noise and contrast ratio , and other metrics, more modern, such as Structural Similarity Index and, Measures Distance , singular value decomposition of the image matrix and Correlation and Spectral Measurements. It also makes a review of physical approaches for predicting image quality from use mathematical observers as the Hotelling and Hotelling Pipeline with Gabor functions or Laguerre - Gauss polynomials . Finally the correlation of these objective methods with subjective assessment of image quality made ​​from ROC analysis based on Diagnostic Performance Curves is analyzed. (author)

  2. Multi-modal and targeted imaging improves automated mid-brain segmentation

    Science.gov (United States)

    Plassard, Andrew J.; D'Haese, Pierre F.; Pallavaram, Srivatsan; Newton, Allen T.; Claassen, Daniel O.; Dawant, Benoit M.; Landman, Bennett A.

    2017-02-01

    The basal ganglia and limbic system, particularly the thalamus, putamen, internal and external globus pallidus, substantia nigra, and sub-thalamic nucleus, comprise a clinically relevant signal network for Parkinson's disease. In order to manually trace these structures, a combination of high-resolution and specialized sequences at 7T are used, but it is not feasible to scan clinical patients in those scanners. Targeted imaging sequences at 3T such as F-GATIR, and other optimized inversion recovery sequences, have been presented which enhance contrast in a select group of these structures. In this work, we show that a series of atlases generated at 7T can be used to accurately segment these structures at 3T using a combination of standard and optimized imaging sequences, though no one approach provided the best result across all structures. In the thalamus and putamen, a median Dice coefficient over 0.88 and a mean surface distance less than 1.0mm was achieved using a combination of T1 and an optimized inversion recovery imaging sequences. In the internal and external globus pallidus a Dice over 0.75 and a mean surface distance less than 1.2mm was achieved using a combination of T1 and FGATIR imaging sequences. In the substantia nigra and sub-thalamic nucleus a Dice coefficient of over 0.6 and a mean surface distance of less than 1.0mm was achieved using the optimized inversion recovery imaging sequence. On average, using T1 and optimized inversion recovery together produced significantly improved segmentation results than any individual modality (p<0.05 wilcox sign-rank test).

  3. Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

    Science.gov (United States)

    Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

    2018-01-01

    An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

  4. On Scientific Data and Image Compression Based on Adaptive Higher-Order FEM

    Czech Academy of Sciences Publication Activity Database

    Šolín, Pavel; Andrš, David

    2009-01-01

    Roč. 1, č. 1 (2009), s. 56-68 ISSN 2070-0733 R&D Projects: GA ČR(CZ) GA102/07/0496; GA AV ČR IAA100760702 Institutional research plan: CEZ:AV0Z20570509 Keywords : data compress ion * image compress ion * adaptive hp-FEM Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering http://www.global-sci.org/aamm

  5. A parallelizable compression scheme for Monte Carlo scatter system matrices in PET image reconstruction

    International Nuclear Information System (INIS)

    Rehfeld, Niklas; Alber, Markus

    2007-01-01

    Scatter correction techniques in iterative positron emission tomography (PET) reconstruction increasingly utilize Monte Carlo (MC) simulations which are very well suited to model scatter in the inhomogeneous patient. Due to memory constraints the results of these simulations are not stored in the system matrix, but added or subtracted as a constant term or recalculated in the projector at each iteration. This implies that scatter is not considered in the back-projector. The presented scheme provides a method to store the simulated Monte Carlo scatter in a compressed scatter system matrix. The compression is based on parametrization and B-spline approximation and allows the formation of the scatter matrix based on low statistics simulations. The compression as well as the retrieval of the matrix elements are parallelizable. It is shown that the proposed compression scheme provides sufficient compression so that the storage in memory of a scatter system matrix for a 3D scanner is feasible. Scatter matrices of two different 2D scanner geometries were compressed and used for reconstruction as a proof of concept. Compression ratios of 0.1% could be achieved and scatter induced artifacts in the images were successfully reduced by using the compressed matrices in the reconstruction algorithm

  6. Least median of squares filtering of locally optimal point matches for compressible flow image registration

    International Nuclear Information System (INIS)

    Castillo, Edward; Guerrero, Thomas; Castillo, Richard; White, Benjamin; Rojo, Javier

    2012-01-01

    Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. (paper)

  7. A novel 3D volumetric voxel registration technique for volume-view-guided image registration of multiple imaging modalities

    International Nuclear Information System (INIS)

    Li Guang; Xie Huchen; Ning, Holly; Capala, Jacek; Arora, Barbara C.; Coleman, C. Norman; Camphausen, Kevin; Miller, Robert W.

    2005-01-01

    Purpose: To provide more clinically useful image registration with improved accuracy and reduced time, a novel technique of three-dimensional (3D) volumetric voxel registration of multimodality images is developed. Methods and Materials: This technique can register up to four concurrent images from multimodalities with volume view guidance. Various visualization effects can be applied, facilitating global and internal voxel registration. Fourteen computed tomography/magnetic resonance (CT/MR) image sets and two computed tomography/positron emission tomography (CT/PET) image sets are used. For comparison, an automatic registration technique using maximization of mutual information (MMI) and a three-orthogonal-planar (3P) registration technique are used. Results: Visually sensitive registration criteria for CT/MR and CT/PET have been established, including the homogeneity of color distribution. Based on the registration results of 14 CT/MR images, the 3D voxel technique is in excellent agreement with the automatic MMI technique and is indicatory of a global positioning error (defined as the means and standard deviations of the error distribution) using the 3P pixel technique: 1.8 deg ± 1.2 deg in rotation and 2.0 ± 1.3 (voxel unit) in translation. To the best of our knowledge, this is the first time that such positioning error has been addressed. Conclusion: This novel 3D voxel technique establishes volume-view-guided image registration of up to four modalities. It improves registration accuracy with reduced time, compared with the 3P pixel technique. This article suggests that any interactive and automatic registration should be safeguarded using the 3D voxel technique

  8. Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

    Science.gov (United States)

    Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

    2017-07-01

    The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

  9. A MODIFIED EMBEDDED ZERO-TREE WAVELET METHOD FOR MEDICAL IMAGE COMPRESSION

    Directory of Open Access Journals (Sweden)

    T. Celine Therese Jenny

    2010-11-01

    Full Text Available The Embedded Zero-tree Wavelet (EZW is a lossy compression method that allows for progressive transmission of a compressed image. By exploiting the natural zero-trees found in a wavelet decomposed image, the EZW algorithm is able to encode large portions of insignificant regions of an still image with a minimal number of bits. The upshot of this encoding is an algorithm that is able to achieve relatively high peak signal to noise ratios (PSNR for high compression levels. The EZW algorithm is to encode large portions of insignificant regions of an image with a minimal number of bits. Vector Quantization (VQ method can be performed as a post processing step to reduce the coded file size. Vector Quantization (VQ method can be reduces redundancy of the image data in order to be able to store or transmit data in an efficient form. It is demonstrated by experimental results that the proposed method outperforms several well-known lossless image compression techniques for still images that contain 256 colors or less.

  10. vECTlab-A fully integrated multi-modality Monte Carlo simulation framework for the radiological imaging sciences

    International Nuclear Information System (INIS)

    Peter, Joerg; Semmler, Wolfhard

    2007-01-01

    Alongside and in part motivated by recent advances in molecular diagnostics, the development of dual-modality instruments for patient and dedicated small animal imaging has gained attention by diverse research groups. The desire for such systems is high not only to link molecular or functional information with the anatomical structures, but also for detecting multiple molecular events simultaneously at shorter total acquisition times. While PET and SPECT have been integrated successfully with X-ray CT, the advance of optical imaging approaches (OT) and the integration thereof into existing modalities carry a high application potential, particularly for imaging small animals. A multi-modality Monte Carlo (MC) simulation approach at present has been developed that is able to trace high-energy (keV) as well as optical (eV) photons concurrently within identical phantom representation models. We show that the involved two approaches for ray-tracing keV and eV photons can be integrated into a unique simulation framework which enables both photon classes to be propagated through various geometry models representing both phantoms and scanners. The main advantage of such integrated framework for our specific application is the investigation of novel tomographic multi-modality instrumentation intended for in vivo small animal imaging through time-resolved MC simulation upon identical phantom geometries. Design examples are provided for recently proposed SPECT-OT and PET-OT imaging systems

  11. Interleaved EPI diffusion imaging using SPIRiT-based reconstruction with virtual coil compression.

    Science.gov (United States)

    Dong, Zijing; Wang, Fuyixue; Ma, Xiaodong; Zhang, Zhe; Dai, Erpeng; Yuan, Chun; Guo, Hua

    2018-03-01

    To develop a novel diffusion imaging reconstruction framework based on iterative self-consistent parallel imaging reconstruction (SPIRiT) for multishot interleaved echo planar imaging (iEPI), with computation acceleration by virtual coil compression. As a general approach for autocalibrating parallel imaging, SPIRiT improves the performance of traditional generalized autocalibrating partially parallel acquisitions (GRAPPA) methods in that the formulation with self-consistency is better conditioned, suggesting SPIRiT to be a better candidate in k-space-based reconstruction. In this study, a general SPIRiT framework is adopted to incorporate both coil sensitivity and phase variation information as virtual coils and then is applied to 2D navigated iEPI diffusion imaging. To reduce the reconstruction time when using a large number of coils and shots, a novel shot-coil compression method is proposed for computation acceleration in Cartesian sampling. Simulations and in vivo experiments were conducted to evaluate the performance of the proposed method. Compared with the conventional coil compression, the shot-coil compression achieved higher compression rates with reduced errors. The simulation and in vivo experiments demonstrate that the SPIRiT-based reconstruction outperformed the existing method, realigned GRAPPA, and provided superior images with reduced artifacts. The SPIRiT-based reconstruction with virtual coil compression is a reliable method for high-resolution iEPI diffusion imaging. Magn Reson Med 79:1525-1531, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  12. Comparison of 3D computer-aided with manual cerebral aneurysm measurements in different imaging modalities

    International Nuclear Information System (INIS)

    Groth, M.; Buhk, J.H.; Schoenfeld, M.; Goebell, E.; Fiehler, J.; Forkert, N.D.

    2013-01-01

    To compare intra- and inter-observer reliability of aneurysm measurements obtained by a 3D computer-aided technique with standard manual aneurysm measurements in different imaging modalities. A total of 21 patients with 29 cerebral aneurysms were studied. All patients underwent digital subtraction angiography (DSA), contrast-enhanced (CE-MRA) and time-of-flight magnetic resonance angiography (TOF-MRA). Aneurysm neck and depth diameters were manually measured by two observers in each modality. Additionally, semi-automatic computer-aided diameter measurements were performed using 3D vessel surface models derived from CE- (CE-com) and TOF-MRA (TOF-com) datasets. Bland-Altman analysis (BA) and intra-class correlation coefficient (ICC) were used to evaluate intra- and inter-observer agreement. BA revealed the narrowest relative limits of intra- and inter-observer agreement for aneurysm neck and depth diameters obtained by TOF-com (ranging between ±5.3 % and ±28.3 %) and CE-com (ranging between ±23.3 % and ±38.1 %). Direct measurements in DSA, TOF-MRA and CE-MRA showed considerably wider limits of agreement. The highest ICCs were observed for TOF-com and CE-com (ICC values, 0.92 or higher for intra- as well as inter-observer reliability). Computer-aided aneurysm measurement in 3D offers improved intra- and inter-observer reliability and a reproducible parameter extraction, which may be used in clinical routine and as objective surrogate end-points in clinical trials. (orig.)

  13. Diffusion-Weighted Imaging for Predicting New Compression Fractures Following Percutaneous Vertebroplasty

    International Nuclear Information System (INIS)

    Sugimoto, T.

    2008-01-01

    Background: Percutaneous vertebroplasty (PVP) is a technique that structurally stabilizes a fractured vertebral body. However, some patients return to the hospital due to recurrent back pain following PVP, and such pain is sometimes caused by new compression fractures. Purpose: To investigate whether the apparent diffusion coefficient (ADC) of adjacent vertebral bodies as assessed by diffusion-weighted imaging before PVP could predict the onset of new compression fractures following PVP. Material and Methods: 25 patients with osteoporotic compression fractures who underwent PVP were enrolled in this study. ADC was measured for 49 vertebral bodies immediately above and below each vertebral body injected with bone cement before and after PVP. By measuring ADC for each adjacent vertebral body, ADC was compared between vertebral bodies with a new compression fracture within 1 month and those without new compression fractures. In addition, the mean ADC of adjacent vertebral bodies per patient was calculated. Results: Mean preoperative ADC for the six adjacent vertebral bodies with new compression fractures was 0.55x10 -3 mm 2 /s (range 0.36-1.01x10 -3 mm 2 /s), and for the 43 adjacent vertebral bodies without new compression fractures 0.20x10 -3 mm 2 /s (range 0-0.98x10 -3 mm 2 /s) (P -3 mm 2 /s (range 0.21-1.01x10 -3 mm 2 /s), and that for the 19 patients without new compression fractures 0.17x10 -3 mm 2 /s (range 0.01-0.43x10 -3 mm 2 /s) (P<0.001). Conclusion: The ADC of adjacent vertebral bodies as assessed by diffusion-weighted imaging before PVP might be one of the predictors for new compression fractures following PVP

  14. Simultaneous optical image compression and encryption using error-reduction phase retrieval algorithm

    International Nuclear Information System (INIS)

    Liu, Wei; Liu, Shutian; Liu, Zhengjun

    2015-01-01

    We report a simultaneous image compression and encryption scheme based on solving a typical optical inverse problem. The secret images to be processed are multiplexed as the input intensities of a cascaded diffractive optical system. At the output plane, a compressed complex-valued data with a lot fewer measurements can be obtained by utilizing error-reduction phase retrieval algorithm. The magnitude of the output image can serve as the final ciphertext while its phase serves as the decryption key. Therefore the compression and encryption are simultaneously completed without additional encoding and filtering operations. The proposed strategy can be straightforwardly applied to the existing optical security systems that involve diffraction and interference. Numerical simulations are performed to demonstrate the validity and security of the proposal. (paper)

  15. Spotting Separator Points at Line Terminals in Compressed Document Images for Text-line Segmentation

    OpenAIRE

    R, Amarnath; Nagabhushan, P.

    2017-01-01

    Line separators are used to segregate text-lines from one another in document image analysis. Finding the separator points at every line terminal in a document image would enable text-line segmentation. In particular, identifying the separators in handwritten text could be a thrilling exercise. Obviously it would be challenging to perform this in the compressed version of a document image and that is the proposed objective in this research. Such an effort would prevent the computational burde...

  16. An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT).

    Science.gov (United States)

    Li, Ran; Duan, Xiaomeng; Li, Xu; He, Wei; Li, Yanling

    2018-04-17

    Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.

  17. An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT

    Directory of Open Access Journals (Sweden)

    Ran Li

    2018-04-01

    Full Text Available Aimed at a low-energy consumption of Green Internet of Things (IoT, this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.

  18. Medical image compression based on vector quantization with variable block sizes in wavelet domain.

    Science.gov (United States)

    Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

    2012-01-01

    An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

  19. Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Huiyan Jiang

    2012-01-01

    Full Text Available An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

  20. Support for Implications of Compressive Sensing Concepts to Imaging Systems

    Science.gov (United States)

    2015-08-02

    Justin Romberg Georgia Tech jrom@ece.gatech.edu Emil Sidky University of Chicago sidky@uchicago.edu Michael Stenner MITRE mstenner@mitre.org Lei Tian...assessment of image quality. Michael Stenner Michael has broad interests in optical imaging, sensing, and communications, and is published in such

  1. Clinical evaluation of the JPEG2000 compression rate of CT and MR images for long term archiving in PACS

    International Nuclear Information System (INIS)

    Cha, Soon Joo; Kim, Sung Hwan; Kim, Yong Hoon

    2006-01-01

    We wanted to evaluate an acceptable compression rate of JPEG2000 for long term archiving of CT and MR images in PACS. Nine CT images and 9 MR images that had small or minimal lesions were randomly selected from the PACS at our institute. All the images are compressed with rates of 5:1, 10:1, 20:1, 40:1 and 80:1 by the JPEG2000 compression protocol. Pairs of original and compressed images were compared by 9 radiologists who were working independently. We designed a JPEG2000 viewing program for comparing two images on one monitor system for performing easy and quick evaluation. All the observers performed the comparison study twice on 5 mega pixel grey scale LCD monitors and 2 mega pixel color LCD monitors, respectively. The PSNR (Peak Signal to Noise Ratio) values were calculated for making quantitative comparisions. On MR and CT, all the images with 5:1 compression images showed no difference from the original images by all 9 observers and only one observer could detect a image difference on one CT image for 10:1 compression on only the 5 mega pixel monitor. For the 20:1 compression rate, clinically significant image deterioration was found in 50% of the images on the 5M pixel monitor study, and in 30% of the images on the 2M pixel monitor. PSNR values larger than 44 dB were calculated for all the compressed images. The clinically acceptable image compression rate for long term archiving by the JPEG2000 compression protocol is 10:1 for MR and CT, and if this is applied to PACS, it would reduce the cost and responsibility of the system

  2. Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression

    Science.gov (United States)

    Daly, Scott J.

    1989-08-01

    The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.

  3. Medical Image Compression Based on Region of Interest, With Application to Colon CT Images

    National Research Council Canada - National Science Library

    Gokturk, Salih

    2001-01-01

    ...., in diagnostically important regions. This paper discusses a hybrid model of lossless compression in the region of interest, with high-rate, motion-compensated, lossy compression in other regions...

  4. Role of magnetic resonance imaging in entrapment and compressive neuropathy - what, where, and how to see the peripheral nerves on the musculoskeletal magnetic resonance image: Part 2. Upper extremity

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sungjun [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea); Hanyang University, Kuri Hospital, Department of Diagnostic Radiology, College of Medicine, Kuri City, Kyunggi-do (Korea); Choi, Jin-Young; Huh, Yong-Min; Song, Ho-Taek; Lee, Sung-Ah [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea); Kim, Seung Min [Yonsei University, Department of Neurology, College of Medicine, Seoul (Korea); Suh, Jin-Suck [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea); Yonsei University, Research Institute of Radiological Science, College of Medicine, Seoul (Korea)

    2007-02-15

    The diagnosis of nerve entrapment and compressive neuropathy has been traditionally based on the clinical and electrodiagnostic examinations. As a result of improvements in the magnetic resonance (MR) imaging modality, it plays not only a fundamental role in the detection of space-occupying lesions, but also a compensatory role in clinically and electrodiagnostically inconclusive cases. Although ultrasound has undergone further development in the past decades and shows high resolution capabilities, it has inherent limitations due to its operator dependency. We review the course of normal peripheral nerves, as well as various clinical demonstrations and pathological features of compressed and entrapped nerves in the upper extremities on MR imaging, according to the nerves involved. The common sites of nerve entrapment of the upper extremity are as follows: the brachial plexus of the thoracic outlet; axillary nerve of the quadrilateral space; radial nerve of the radial tunnel; ulnar nerve of the cubital tunnel and Guyon's canal; median nerve of the pronator syndrome, anterior interosseous nerve syndrome, and carpal tunnel syndrome. Although MR imaging can depict the peripheral nerves in the extremities effectively, radiologists should be familiar with nerve pathways, common sites of nerve compression, and common space-occupying lesions resulting in nerve compression in MR imaging. (orig.)

  5. Role of magnetic resonance imaging in entrapment and compressive neuropathy - what, where, and how to see the peripheral nerves on the musculoskeletal magnetic resonance image: Part 2. Upper extremity

    International Nuclear Information System (INIS)

    Kim, Sungjun; Choi, Jin-Young; Huh, Yong-Min; Song, Ho-Taek; Lee, Sung-Ah; Kim, Seung Min; Suh, Jin-Suck

    2007-01-01

    The diagnosis of nerve entrapment and compressive neuropathy has been traditionally based on the clinical and electrodiagnostic examinations. As a result of improvements in the magnetic resonance (MR) imaging modality, it plays not only a fundamental role in the detection of space-occupying lesions, but also a compensatory role in clinically and electrodiagnostically inconclusive cases. Although ultrasound has undergone further development in the past decades and shows high resolution capabilities, it has inherent limitations due to its operator dependency. We review the course of normal peripheral nerves, as well as various clinical demonstrations and pathological features of compressed and entrapped nerves in the upper extremities on MR imaging, according to the nerves involved. The common sites of nerve entrapment of the upper extremity are as follows: the brachial plexus of the thoracic outlet; axillary nerve of the quadrilateral space; radial nerve of the radial tunnel; ulnar nerve of the cubital tunnel and Guyon's canal; median nerve of the pronator syndrome, anterior interosseous nerve syndrome, and carpal tunnel syndrome. Although MR imaging can depict the peripheral nerves in the extremities effectively, radiologists should be familiar with nerve pathways, common sites of nerve compression, and common space-occupying lesions resulting in nerve compression in MR imaging. (orig.)

  6. Video compression and DICOM proxies for remote viewing of DICOM images

    Science.gov (United States)

    Khorasani, Elahe; Sheinin, Vadim; Paulovicks, Brent; Jagmohan, Ashish

    2009-02-01

    Digital medical images are rapidly growing in size and volume. A typical study includes multiple image "slices." These images have a special format and a communication protocol referred to as DICOM (Digital Imaging Communications in Medicine). Storing, retrieving, and viewing these images are handled by DICOM-enabled systems. DICOM images are stored in central repository servers called PACS (Picture Archival and Communication Systems). Remote viewing stations are DICOM-enabled applications that can query the PACS servers and retrieve the DICOM images for viewing. Modern medical images are quite large, reaching as much as 1 GB per file. When the viewing station is connected to the PACS server via a high-bandwidth local LAN, downloading of the images is relatively efficient and does not cause significant wasted time for physicians. Problems arise when the viewing station is located in a remote facility that has a low-bandwidth link to the PACS server. If the link between the PACS and remote facility is in the range of 1 Mbit/sec, downloading medical images is very slow. To overcome this problem, medical images are compressed to reduce the size for transmission. This paper describes a method of compression that maintains diagnostic quality of images while significantly reducing the volume to be transmitted, without any change to the existing PACS servers and viewer software, and without requiring any change in the way doctors retrieve and view images today.

  7. Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging.

    Directory of Open Access Journals (Sweden)

    Danuta M Sampson

    Full Text Available To present en face optical coherence tomography (OCT images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities.En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO and microperimetry.Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE pathology due to segmentation error at the level of Bruch's membrane (BM. Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities.Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis.

  8. A System for Compressive Spectral and Polarization Imaging at Short Wave Infrared (SWIR) Wavelengths

    Science.gov (United States)

    2017-10-18

    UV -­‐ VIS -­‐IR   60mm   Apo   Macro  lens   Jenoptik-­‐Inc   $5,817.36   IR... VIS /NIR Compressive Spectral Imager”, Proceedings of IEEE International Conference on Image Processing (ICIP ’15), Quebec City, Canada, (September...imaging   system   will   lead   to   a   wide-­‐band   VIS -­‐NIR-­‐SWIR   compressive  spectral  and  polarimetric

  9. Data Compression of Seismic Images by Neural Networks Compression d'images sismiques par des réseaux neuronaux

    Directory of Open Access Journals (Sweden)

    Epping W. J. M.

    2006-11-01

    Full Text Available Neural networks with the multi-layered perceptron architecture were trained on an autoassociation task to compress 2D seismic data. Networks with linear transfer functions outperformed nonlinear neural nets with single or multiple hidden layers. This indicates that the correlational structure of the seismic data is predominantly linear. A compression factor of 5 to 7 can be achieved if a reconstruction error of 10% is allowed. The performance on new test data was similar to that achieved with the training data. The hidden units developed feature-detecting properties that resemble oriented line, edge and more complex feature detectors. The feature detectors of linear neural nets are near-orthogonal rotations of the principal eigenvectors of the Karhunen-Loève transformation. Des réseaux neuronaux à architecture de perceptron multicouches ont été expérimentés en auto-association pour permettre la compression de données sismiques bidimensionnelles. Les réseaux neuronaux à fonctions de transfert linéaires s'avèrent plus performants que les réseaux neuronaux non linéaires, à une ou plusieurs couches cachées. Ceci indique que la structure corrélative des données sismiques est à prédominance linéaire. Un facteur de compression de 5 à 7 peut être obtenu si une erreur de reconstruction de 10 % est admise. La performance sur les données de test est très proche de celle obtenue sur les données d'apprentissage. Les unités cachées développent des propriétés de détection de caractéristiques ressemblant à des détecteurs de lignes orientées, de bords et de figures plus complexes. Les détecteurs de caractéristique des réseaux neuronaux linéaires sont des rotations quasi orthogonales des vecteurs propres principaux de la transformation de Karhunen-Loève.

  10. A progressive data compression scheme based upon adaptive transform coding: Mixture block coding of natural images

    Science.gov (United States)

    Rost, Martin C.; Sayood, Khalid

    1991-01-01

    A method for efficiently coding natural images using a vector-quantized variable-blocksized transform source coder is presented. The method, mixture block coding (MBC), incorporates variable-rate coding by using a mixture of discrete cosine transform (DCT) source coders. Which coders are selected to code any given image region is made through a threshold driven distortion criterion. In this paper, MBC is used in two different applications. The base method is concerned with single-pass low-rate image data compression. The second is a natural extension of the base method which allows for low-rate progressive transmission (PT). Since the base method adapts easily to progressive coding, it offers the aesthetic advantage of progressive coding without incorporating extensive channel overhead. Image compression rates of approximately 0.5 bit/pel are demonstrated for both monochrome and color images.

  11. Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

    Science.gov (United States)

    August, Isaac; Oiknine, Yaniv; Abuleil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

    2016-03-01

    Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

  12. Blind Compressed Image Watermarking for Noisy Communication Channels

    Science.gov (United States)

    2015-10-26

    Lenna test image [11] for our simulations, and gradient projection for sparse recon- struction (GPSR) [12] to solve the convex optimization prob- lem...E. Candes, J. Romberg , and T. Tao, “Robust uncertainty prin- ciples: exact signal reconstruction from highly incomplete fre- quency information,” IEEE...Images - Requirements and Guidelines,” ITU-T Recommen- dation T.81, 1992. [6] M. Gkizeli, D. Pados, and M. Medley, “Optimal signature de - sign for

  13. VLSI ARCHITECTURE FOR IMAGE COMPRESSION THROUGH ADDER MINIMIZATION TECHNIQUE AT DCT STRUCTURE

    Directory of Open Access Journals (Sweden)

    N.R. Divya

    2014-08-01

    Full Text Available Data compression plays a vital role in multimedia devices to present the information in a succinct frame. Initially, the DCT structure is used for Image compression, which has lesser complexity and area efficient. Similarly, 2D DCT also has provided reasonable data compression, but implementation concern, it calls more multipliers and adders thus its lead to acquire more area and high power consumption. To contain an account of all, this paper has been dealt with VLSI architecture for image compression using Rom free DA based DCT (Discrete Cosine Transform structure. This technique provides high-throughput and most suitable for real-time implementation. In order to achieve this image matrix is subdivided into odd and even terms then the multiplication functions are removed by shift and add approach. Kogge_Stone_Adder techniques are proposed for obtaining a bit-wise image quality which determines the new trade-off levels as compared to the previous techniques. Overall the proposed architecture produces reduced memory, low power consumption and high throughput. MATLAB is used as a funding tool for receiving an input pixel and obtaining output image. Verilog HDL is used for implementing the design, Model Sim for simulation, Quatres II is used to synthesize and obtain details about power and area.

  14. Multiband CCD Image Compression for Space Camera with Large Field of View

    Directory of Open Access Journals (Sweden)

    Jin Li

    2014-01-01

    Full Text Available Space multiband CCD camera compression encoder requires low-complexity, high-robustness, and high-performance because of its captured images information being very precious and also because it is usually working on the satellite where the resources, such as power, memory, and processing capacity, are limited. However, the traditional compression approaches, such as JPEG2000, 3D transforms, and PCA, have the high-complexity. The Consultative Committee for Space Data Systems-Image Data Compression (CCSDS-IDC algorithm decreases the average PSNR by 2 dB compared with JPEG2000. In this paper, we proposed a low-complexity compression algorithm based on deep coupling algorithm among posttransform in wavelet domain, compressive sensing, and distributed source coding. In our algorithm, we integrate three low-complexity and high-performance approaches in a deeply coupled manner to remove the spatial redundant, spectral redundant, and bit information redundancy. Experimental results on multiband CCD images show that the proposed algorithm significantly outperforms the traditional approaches.

  15. Spinal cord compression at C1-C2 level due to tophaceous gout (magnetic resonance imaging and computed tomography cisternographic findings)

    International Nuclear Information System (INIS)

    Vries, C. de; Slegte, R.G.M. de; Valk, J.

    1987-01-01

    The authors report a case of spinal cord compression at the level of the foramen magnum due to tophaceous gout in a patient with no clinical history of gout. The presence of a foramen magnum mass due to urate crystal deposition in a patient without clinical history of gout or additional bone abnormalities has, to the best of the authors' knowledge, never been described before. In the case presented here, no bone changes were encountered with CT or MRI. Neither the presence of small high-density punctuations on the CT examination nor the signal intensities of the mass on T1- and T2-weighted images led to the radiological diagnois of tophaceous gout. The foramen magnum mass and the spinal cord compression were, however, beautifully depicted by both modalities. 14 refs.; 2 figs

  16. Single-event transient imaging with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor.

    Science.gov (United States)

    Mochizuki, Futa; Kagawa, Keiichiro; Okihara, Shin-ichiro; Seo, Min-Woong; Zhang, Bo; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

    2016-02-22

    In the work described in this paper, an image reproduction scheme with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor was demonstrated. The sensor captures an object by compressing a sequence of images with focal-plane temporally random-coded shutters, followed by reconstruction of time-resolved images. Because signals are modulated pixel-by-pixel during capturing, the maximum frame rate is defined only by the charge transfer speed and can thus be higher than those of conventional ultra-high-speed cameras. The frame rate and optical efficiency of the multi-aperture scheme are discussed. To demonstrate the proposed imaging method, a 5×3 multi-aperture image sensor was fabricated. The average rising and falling times of the shutters were 1.53 ns and 1.69 ns, respectively. The maximum skew among the shutters was 3 ns. The sensor observed plasma emission by compressing it to 15 frames, and a series of 32 images at 200 Mfps was reconstructed. In the experiment, by correcting disparities and considering temporal pixel responses, artifacts in the reconstructed images were reduced. An improvement in PSNR from 25.8 dB to 30.8 dB was confirmed in simulations.

  17. Assessment of the impact of modeling axial compression on PET image reconstruction.

    Science.gov (United States)

    Belzunce, Martin A; Reader, Andrew J

    2017-10-01

    To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher

  18. Research progress of functional magnetic resonance imaging in cross-modal activation of visual cortex during tactile perception

    International Nuclear Information System (INIS)

    Zhan Jie; Gong Honghan

    2013-01-01

    An increasing amount of neuroimaging studies recently demonstrated activation of visual cortex in both blind and sighted participants when performing a variety of tactile tasks such as Braille reading and tactile object recognition, which indicates that visual cortex not only receives visual information, but may participate in tactile perception. To address these cross-modal changes of visual cortex and the neurophysiological mechanisms, many researchers conducted explosive studies using functional magnetic resonance imaging (fMRI) and have made some achievements. This review focuses on cross-modal activation of visual cortex and the underlying mechanisms during tactile perception in both blind and sighted individuals. (authors)

  19. Effect of image compression and scaling on automated scoring of immunohistochemical stainings and segmentation of tumor epithelium

    Directory of Open Access Journals (Sweden)

    Konsti Juho

    2012-03-01

    Full Text Available Abstract Background Digital whole-slide scanning of tissue specimens produces large images demanding increasing storing capacity. To reduce the need of extensive data storage systems image files can be compressed and scaled down. The aim of this article is to study the effect of different levels of image compression and scaling on automated image analysis of immunohistochemical (IHC stainings and automated tumor segmentation. Methods Two tissue microarray (TMA slides containing 800 samples of breast cancer tissue immunostained against Ki-67 protein and two TMA slides containing 144 samples of colorectal cancer immunostained against EGFR were digitized with a whole-slide scanner. The TMA images were JPEG2000 wavelet compressed with four compression ratios: lossless, and 1:12, 1:25 and 1:50 lossy compression. Each of the compressed breast cancer images was furthermore scaled down either to 1:1, 1:2, 1:4, 1:8, 1:16, 1:32, 1:64 or 1:128. Breast cancer images were analyzed using an algorithm that quantitates the extent of staining in Ki-67 immunostained images, and EGFR immunostained colorectal cancer images were analyzed with an automated tumor segmentation algorithm. The automated tools were validated by comparing the results from losslessly compressed and non-scaled images with results from conventional visual assessments. Percentage agreement and kappa statistics were calculated between results from compressed and scaled images and results from lossless and non-scaled images. Results Both of the studied image analysis methods showed good agreement between visual and automated results. In the automated IHC quantification, an agreement of over 98% and a kappa value of over 0.96 was observed between losslessly compressed and non-scaled images and combined compression ratios up to 1:50 and scaling down to 1:8. In automated tumor segmentation, an agreement of over 97% and a kappa value of over 0.93 was observed between losslessly compressed images and

  20. Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.

    Science.gov (United States)

    Yassin, Nisreen I R; Omran, Shaimaa; El Houby, Enas M F; Allam, Hemat

    2018-03-01

    The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer. The SR was conducted using a comprehensive selection of scientific databases as reference sources, allowing access to diverse publications in the field. The scientific databases used are Springer Link (SL), Science Direct (SD), IEEE Xplore Digital Library, and PubMed. Inclusion and exclusion criteria were defined and applied to each retrieved work to select those of interest. From 320 studies retrieved, 154 studies were included. However, the scope of this research is limited to scientific and academic works and excludes commercial interests. This survey provides a general analysis of the current status of CAD systems according to the used image modalities and the machine learning based classifiers. Potential research studies have been discussed to create a more objective and efficient CAD systems. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

    Directory of Open Access Journals (Sweden)

    Dane Brown

    2017-07-01

    Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

  2. Diagnostic ability of differential diagnosis in ameloblastoma and odontogenic keratocyst by imaging modalities and observers

    International Nuclear Information System (INIS)

    Gang, Tae In; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Kim, Jeong Hwa; Moon, Je Woon; Choi, Soon Chul

    2006-01-01

    To evaluate the diagnostic ability in differentiating between ameloblastoma and odontogenic keratocyst according to the imaging modalities and observes. We evaluated thirty-six cases of ameloblastomas and forty-seven cases of odontogenic keratocysts all histologically confirmed. Six oral and maxillofacial radiologists diagnosed the lesions by 3 methods: using panoramic radiograph, using computed tomograph (CT), and using panoramic radiograph and CT. The observers were classified by 3 groups: group 1 had experienced over 10 years in oral and mazilofacial radiologic field, group 2 had experienced for 3-4 years, and group 3 was in the process of residentship. After over 2 weeks, the observers diagnosed them by the same methods. The ROC curve areas except for group 3 were the highest with interpretation using panoramic radiograph and CT, followed by interpretation using CT only, and the lowest with interpretation using panoramic radiograph only. The overall difference was not found in diagnostic ability among groups in using panoramic radiograph only, but there was difference in diagnostic ability of group 1 and 2 vs 3 in using CT only, and combination panoramic radiograph and CT. To differentiate between ameloblastoma and odontogenic keratocyst more accurately, the experienced oral and maxillofacial radiologist should diagnose with combination of panoramic radiograph and CT

  3. Diagnostic ability of differential diagnosis in ameloblastoma and odontogenic keratocyst by imaging modalities and observers

    Energy Technology Data Exchange (ETDEWEB)

    Gang, Tae In; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Kim, Jeong Hwa; Moon, Je Woon; Choi, Soon Chul [Seoul National Univ. School of Dentistry, Seoul (Korea, Republic of)

    2006-12-15

    To evaluate the diagnostic ability in differentiating between ameloblastoma and odontogenic keratocyst according to the imaging modalities and observes. We evaluated thirty-six cases of ameloblastomas and forty-seven cases of odontogenic keratocysts all histologically confirmed. Six oral and maxillofacial radiologists diagnosed the lesions by 3 methods: using panoramic radiograph, using computed tomograph (CT), and using panoramic radiograph and CT. The observers were classified by 3 groups: group 1 had experienced over 10 years in oral and mazilofacial radiologic field, group 2 had experienced for 3-4 years, and group 3 was in the process of residentship. After over 2 weeks, the observers diagnosed them by the same methods. The ROC curve areas except for group 3 were the highest with interpretation using panoramic radiograph and CT, followed by interpretation using CT only, and the lowest with interpretation using panoramic radiograph only. The overall difference was not found in diagnostic ability among groups in using panoramic radiograph only, but there was difference in diagnostic ability of group 1 and 2 vs 3 in using CT only, and combination panoramic radiograph and CT. To differentiate between ameloblastoma and odontogenic keratocyst more accurately, the experienced oral and maxillofacial radiologist should diagnose with combination of panoramic radiograph and CT.

  4. Faster tissue interface analysis from Raman microscopy images using compressed factorisation

    Science.gov (United States)

    Palmer, Andrew D.; Bannerman, Alistair; Grover, Liam; Styles, Iain B.

    2013-06-01

    The structure of an artificial ligament was examined using Raman microscopy in combination with novel data analysis. Basis approximation and compressed principal component analysis are shown to provide efficient compression of confocal Raman microscopy images, alongside powerful methods for unsupervised analysis. This scheme allows the acceleration of data mining, such as principal component analysis, as they can be performed on the compressed data representation, providing a decrease in the factorisation time of a single image from five minutes to under a second. Using this workflow the interface region between a chemically engineered ligament construct and a bone-mimic anchor was examined. Natural ligament contains a striated interface between the bone and tissue that provides improved mechanical load tolerance, a similar interface was found in the ligament construct.

  5. Magnetic Resonance Imaging versus Computed Tomography and Different Imaging Modalities in Evaluation of Sinonasal Neoplasms Diagnosed by Histopathology

    Directory of Open Access Journals (Sweden)

    Mohammed A. Gomaa

    2013-01-01

    Full Text Available Objective The study purpose was to detect the value of magnetic resonance imaging (MRI compared to computed tomography (CT and different imaging modalities as conventional radiology in evaluation of sinonasal neoplasms diagnosed by Histopathology. Methods Thirty patients (16 males and 14 females were complaining of symptoms related to sinonasal tract. After thorough clinical and local examination, the patients were subjected to the following: conventional radiography, CT, MRI, and histopathological examination. Results The nasal cavity was the most commonly involved site with sinonasal malignancies followed by the maxillary sinuses. The least commonly affected site was the frontal sinuses. Benign sinonasal tumors were present in 14 cases. The most common benign lesion was juvenile nasopharyngeal angiofibroma (6 cases, followed by inverted papilloma (3 cases. While malignant sinonasal tumors were present in 16 cases, squamous cell carcinoma was present in 5 cases, and undifferentiated carcinoma, in 3 cases. Lymphoepithelioma and non-Hodgkin lymphomas were present in 2 cases each, while adenocarcinoma, chondrosarcoma, adenoid cystic carcinoma, and rhabdomyosarcoma were present in 1 case each. Conclusion MRI with its superior soft tissue contrast and multiplanar capability is superior to CT in pretreatment evaluation of primary malignant tumors of sinonasal cavity.

  6. Multi-scale simulations of field ion microscopy images—Image compression with and without the tip shank

    International Nuclear Information System (INIS)

    NiewieczerzaŁ, Daniel; Oleksy, CzesŁaw; Szczepkowicz, Andrzej

    2012-01-01

    Multi-scale simulations of field ion microscopy images of faceted and hemispherical samples are performed using a 3D model. It is shown that faceted crystals have compressed images even in cases with no shank. The presence of the shank increases the compression of images of faceted crystals quantitatively in the same way as for hemispherical samples. It is hereby proven that the shank does not influence significantly the local, relative variations of the magnification caused by the atomic-scale structure of the sample. -- Highlights: ► Multi-scale simulations of field ion microscopy images. ► Faceted and hemispherical samples with and without shank. ► Shank causes overall compression, but does not influence local magnification effects. ► Image compression linearly increases with the shank angle. ► Shank changes compression of image of faceted tip in the same way as for smooth sample.

  7. Application of multi-modality image coregistration in paediatric prosthetic endocarditis

    International Nuclear Information System (INIS)

    Kitsos, T.; Chung, D.K.; Howman-Giles, R.; Lau, Y.H.; University of Technology, Sydney, NSW

    2003-01-01

    This is a case where coregistration of Gallium and chest CT scans provided important clinical information which had a significant impact on management decisions. A 13-year-old girl from Noumea was transferred to our hospital for further management of S.haemolyticus bacteraemia. She had a history of complex congenital heart disease, requiring several cardiac surgical procedures. Seven months earlier she had a patch repair of the ventricular septum and formation of a right ventricle to pulmonary artery conduit. On admission she was generally unwell and had hemoptysis. She had fever to 39.9 deg C, oximetry of 83 per cent on room air, finger clubbing and a cardiac murmur. Chest X-ray and CT scans showed widespread pulmonary consolidation with bilateral pleural effusions. An echocardiogram showed no evidence of endocarditis. The crucial diagnostic dilemma was whether she had pneumonia or prosthetic endocarditis: the latter was more ominous and entailed high risk surgery. A Gallium whole body scan with chest SPECT showed focal localisation in the right mid chest. However, its location could not be confidently defined. A specifically developed computer program was used to co-register the Gallium SPECT and chest CT scans. The co-registered images conclusively localised the Gallium scan lesion to the prosthetic pulmonary outflow conduit, consistent with endocarditis. This triggered referral for cardiac MRI, which confirmed the diagnosis. In summary co-registration allowed precise structural localisation of focal Gallium uptake in the prosthetic pulmonary outflow conduit, with profound impact on the patient's diagnosis and subsequent management. This is an example of the potential benefits of co-registering structural and functional imaging modalities. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

  8. Alternatives to the discrete cosine transform for irreversible tomographic image compression

    International Nuclear Information System (INIS)

    Villasenor, J.D.

    1993-01-01

    Full-frame irreversible compression of medical images is currently being performed using the discrete cosine transform (DCT). Although the DCT is the optimum fast transform for video compression applications, the authors show here that it is out-performed by the discrete Fourier transform (DFT) and discrete Hartley transform (DHT) for images obtained using positron emission tomography (PET) and magnetic resonance imaging (MRI), and possibly for certain types of digitized radiographs. The difference occurs because PET and MRI images are characterized by a roughly circular region D of non-zero intensity bounded by a region R in which the Image intensity is essentially zero. Clipping R to its minimum extent can reduce the number of low-intensity pixels but the practical requirement that images be stored on a rectangular grid means that a significant region of zero intensity must remain an integral part of the image to be compressed. With this constraint imposed, the DCT loses its advantage over the DFT because neither transform introduces significant artificial discontinuities. The DFT and DHT have the further important advantage of requiring less computation time than the DCT

  9. A Novel Medical Image Watermarking in Three-dimensional Fourier Compressed Domain

    Directory of Open Access Journals (Sweden)

    Baoru Han

    2015-09-01

    Full Text Available Digital watermarking is a research hotspot in the field of image security, which is protected digital image copyright. In order to ensure medical image information security, a novel medical image digital watermarking algorithm in three-dimensional Fourier compressed domain is proposed. The novel medical image digital watermarking algorithm takes advantage of three-dimensional Fourier compressed domain characteristics, Legendre chaotic neural network encryption features and robust characteristics of differences hashing, which is a robust zero-watermarking algorithm. On one hand, the original watermarking image is encrypted in order to enhance security. It makes use of Legendre chaotic neural network implementation. On the other hand, the construction of zero-watermarking adopts differences hashing in three-dimensional Fourier compressed domain. The novel watermarking algorithm does not need to select a region of interest, can solve the problem of medical image content affected. The specific implementation of the algorithm and the experimental results are given in the paper. The simulation results testify that the novel algorithm possesses a desirable robustness to common attack and geometric attack.

  10. Grid-Independent Compressive Imaging and Fourier Phase Retrieval

    Science.gov (United States)

    Liao, Wenjing

    2013-01-01

    This dissertation is composed of two parts. In the first part techniques of band exclusion(BE) and local optimization(LO) are proposed to solve linear continuum inverse problems independently of the grid spacing. The second part is devoted to the Fourier phase retrieval problem. Many situations in optics, medical imaging and signal processing call…

  11. Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

    Science.gov (United States)

    Zhang, Jin-Yu; Meng, Xiang-Bing; Xu, Wei; Zhang, Wei; Zhang, Yong

    2014-01-01

    This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method. PMID:24696649

  12. Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

    Directory of Open Access Journals (Sweden)

    Jin-Yu Zhang

    2014-01-01

    Full Text Available This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method.

  13. Diagnosis of Alzheimer's disease using brain perfusion SPECT and MR imaging: which modality achieves better diagnostic accuracy?

    International Nuclear Information System (INIS)

    Kubota, Takao; Ushijima, Yo; Yamada, Kei; Okuyama, Chio; Kizu, Osamu; Nishimura, Tsunehiko

    2005-01-01

    The purpose of this study was to compare the accuracy of MR imaging and brain perfusion single-photon emission tomography (SPECT) in diagnosing Alzheimer's disease (AD). The transaxial section display of brain perfusion SPECT, three-dimensional stereotactic surface projection (3D-SSP) SPECT image sets, thin-section MR imaging of the hippocampus and perfusion MR imaging were evaluated in 66 subjects comprising 35 AD patients and 31 subjects without AD. SPECT and MR imaging were visually interpreted by two experts and two novices, and the diagnostic ability of each modality was evaluated by receiver operating characteristic (ROC) analysis. In the experts' interpretations, there was no significant difference in the area under the ROC curve (A z ) between 3D-SSP and thin-section MR imaging, whereas the A z of transaxial SPECT display was significantly lower than that of 3D-SSP (3D-SSP: 0.97, thin-section MR imaging: 0.96, transaxial SPECT: 0.91), and the A z of perfusion MR imaging was lowest (0.63). The sensitivity and specificity of each modality were, respectively, 80.0% and 96.8% for 3D-SSP, 77.1% and 96.8% for thin-section MR imaging, 60.0% and 93.5% for transaxial SPECT display and 34.3% and 100% for perfusion MR imaging. In the novices' interpretations, the A z , sensitivity and specificity of 3D-SSP were superior to those of thin-section MR imaging. Thin-section hippocampal MR imaging and 3D-SSP image sets had potentially equivalent value for the diagnosis of AD, and they were superior to transaxial SPECT display and perfusion MR imaging. For avoidance of the effect of interpreters' experience on image evaluation, 3D-SSP appears to be optimal. (orig.)

  14. Quality Evaluation and Nonuniform Compression of Geometrically Distorted Images Using the Quadtree Distortion Map

    Directory of Open Access Journals (Sweden)

    Cristina Costa

    2004-09-01

    Full Text Available The paper presents an analysis of the effects of lossy compression algorithms applied to images affected by geometrical distortion. It will be shown that the encoding-decoding process results in a nonhomogeneous image degradation in the geometrically corrected image, due to the different amount of information associated to each pixel. A distortion measure named quadtree distortion map (QDM able to quantify this aspect is proposed. Furthermore, QDM is exploited to achieve adaptive compression of geometrically distorted pictures, in order to ensure a uniform quality on the final image. Tests are performed using JPEG and JPEG2000 coding standards in order to quantitatively and qualitatively assess the performance of the proposed method.

  15. Single-photon compressive imaging with some performance benefits over raster scanning

    International Nuclear Information System (INIS)

    Yu, Wen-Kai; Liu, Xue-Feng; Yao, Xu-Ri; Wang, Chao; Zhai, Guang-Jie; Zhao, Qing

    2014-01-01

    A single-photon imaging system based on compressed sensing has been developed to image objects under ultra-low illumination. With this system, we have successfully realized imaging at the single-photon level with a single-pixel avalanche photodiode without point-by-point raster scanning. From analysis of the signal-to-noise ratio in the measurement we find that our system has much higher sensitivity than conventional ones based on point-by-point raster scanning, while the measurement time is also reduced. - Highlights: • We design a single photon imaging system with compressed sensing. • A single point avalanche photodiode is used without raster scanning. • The Poisson shot noise in the measurement is analyzed. • The sensitivity of our system is proved to be higher than that of raster scanning

  16. Methylene blue microbubbles as a model dual-modality contrast agent for ultrasound and activatable photoacoustic imaging

    Science.gov (United States)

    Jeon, Mansik; Song, Wentao; Huynh, Elizabeth; Kim, Jungho; Kim, Jeesu; Helfield, Brandon L.; Leung, Ben Y. C.; Goertz, David E.; Zheng, Gang; Oh, Jungtaek; Lovell, Jonathan F.; Kim, Chulhong

    2014-01-01

    Ultrasound and photoacoustic imaging are highly complementary modalities since both use ultrasonic detection for operation. Increasingly, photoacoustic and ultrasound have been integrated in terms of hardware instrumentation. To generate a broadly accessible dual-modality contrast agent, we generated microbubbles (a standard ultrasound contrast agent) in a solution of methylene blue (a standard photoacoustic dye). This MB2 solution was formed effectively and was optimized as a dual-modality contrast solution. As microbubble concentration increased (with methylene blue concentration constant), photoacoustic signal was attenuated in the MB2 solution. When methylene blue concentration increased (with microbubble concentration held constant), no ultrasonic interference was observed. Using an MB2 solution that strongly attenuated all photoacoustic signal, high powered ultrasound could be used to burst the microbubbles and dramatically enhance photoacoustic contrast (>800-fold increase), providing a new method for spatiotemporal control of photoacoustic signal generation.

  17. High bit depth infrared image compression via low bit depth codecs

    DEFF Research Database (Denmark)

    Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

    .264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can...

  18. On the Separation of Quantum Noise for Cardiac X-Ray Image Compression

    NARCIS (Netherlands)

    de Bruijn, F.J.; Slump, Cornelis H.

    1996-01-01

    In lossy medical image compression, the requirements for the preservation of diagnostic integrity cannot be easily formulated in terms of a perceptual model. Especially, since human visual perception is dependent on numerous factors such as the viewing conditions and psycho-visual factors.

  19. DSP accelerator for the wavelet compression/decompression of high- resolution images

    Energy Technology Data Exchange (ETDEWEB)

    Hunt, M.A.; Gleason, S.S.; Jatko, W.B.

    1993-07-23

    A Texas Instruments (TI) TMS320C30-based S-Bus digital signal processing (DSP) module was used to accelerate a wavelet-based compression and decompression algorithm applied to high-resolution fingerprint images. The law enforcement community, together with the National Institute of Standards and Technology (NISI), is adopting a standard based on the wavelet transform for the compression, transmission, and decompression of scanned fingerprint images. A two-dimensional wavelet transform of the input image is computed. Then spatial/frequency regions are automatically analyzed for information content and quantized for subsequent Huffman encoding. Compression ratios range from 10:1 to 30:1 while maintaining the level of image quality necessary for identification. Several prototype systems were developed using SUN SPARCstation 2 with a 1280 {times} 1024 8-bit display, 64-Mbyte random access memory (RAM), Tiber distributed data interface (FDDI), and Spirit-30 S-Bus DSP-accelerators from Sonitech. The final implementation of the DSP-accelerated algorithm performed the compression or decompression operation in 3.5 s per print. Further increases in system throughput were obtained by adding several DSP accelerators operating in parallel.

  20. No Reference Prediction of