Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

Directory of Open Access Journals (Sweden)

YiNan Zhang

2017-01-01

Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

TU-G-BRA-08: BEST IN PHYSICS (JOINT IMAGING-THERAPY): Hybrid PET-MRI Imaging of Acute Radiation Induced Cardiac Toxicity

International Nuclear Information System (INIS)

El-Sherif, O; Xhaferllari, I; Gaede, S; Sykes, J; Butler, J; Wisenberg, G; Prato, F

2015-01-01

Purpose: To identify the presence of low-dose radiation induced cardiac toxicity in a canine model using hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI). Methods: Research ethics board approval was obtained for a longitudinal imaging study of 5 canines after cardiac irradiation. Animals were imaged at baseline, 1 week post cardiac irradiation, and 1 month post cardiac irradiation using a hybrid PET- MRI system (Biograph mMR, Siemens Healthcare). The imaging protocol was designed to assess acute changes in myocardial perfusion and inflammation. Myocardial perfusion imaging was performed using N13-ammonia tracer followed by a dynamic PET acquisition scan. A compartmental tracer kinetic model was used for absolute perfusion quantification. Myocardial inflammation imaging was performed using F18-fluorodeoxyglucose (FDG) tracer. The standard uptake value (SUV) over a region encompassing the whole heart was used to compare FDG scans. All animals received a simulation CT scan (GE Medical Systems) for radiation treatment planning. Radiation treatment plans were created using the Pinncale3 treatment planning system (Philips Radiation Oncology Systems) and designed to resemble the typical cardiac exposure during left-sided breast cancer radiotherapy. Cardiac irradiations were performed in a single fraction using a TrueBeam linear accelerator (Varian Medical Systems). Results: The delivered dose (mean ± standard deviation) to heart was 1.8±0.2 Gy. Reductions in myocardial stress perfusion relative to baseline were observed in 2 of the 5 animals 1 month post radiation. A global inflammatory response 1 month post radiation was observed in 4 of the 5 animals. The calculated SUV at 1 month post radiation was significantly higher (p=0.05) than the baseline SUV. Conclusion: Low doses of cardiac irradiation (< 2 Gy) may lead to myocardial perfusion defects and a global inflammatory response that can be detectable as early as 1 month post irradiation

TU-G-BRA-08: BEST IN PHYSICS (JOINT IMAGING-THERAPY): Hybrid PET-MRI Imaging of Acute Radiation Induced Cardiac Toxicity

Energy Technology Data Exchange (ETDEWEB)

El-Sherif, O; Xhaferllari, I; Gaede, S [Western Univeristy, London, ON (United Kingdom); London Regional Cancer Program, London, ON (United Kingdom); Sykes, J; Butler, J [Lawson Health Research Institute, London, ON (United Kingdom); Wisenberg, G; Prato, F [Western Univeristy, London, ON (United Kingdom); Lawson Health Research Institute, London, ON (United Kingdom)

2015-06-15

Purpose: To identify the presence of low-dose radiation induced cardiac toxicity in a canine model using hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI). Methods: Research ethics board approval was obtained for a longitudinal imaging study of 5 canines after cardiac irradiation. Animals were imaged at baseline, 1 week post cardiac irradiation, and 1 month post cardiac irradiation using a hybrid PET- MRI system (Biograph mMR, Siemens Healthcare). The imaging protocol was designed to assess acute changes in myocardial perfusion and inflammation. Myocardial perfusion imaging was performed using N13-ammonia tracer followed by a dynamic PET acquisition scan. A compartmental tracer kinetic model was used for absolute perfusion quantification. Myocardial inflammation imaging was performed using F18-fluorodeoxyglucose (FDG) tracer. The standard uptake value (SUV) over a region encompassing the whole heart was used to compare FDG scans. All animals received a simulation CT scan (GE Medical Systems) for radiation treatment planning. Radiation treatment plans were created using the Pinncale3 treatment planning system (Philips Radiation Oncology Systems) and designed to resemble the typical cardiac exposure during left-sided breast cancer radiotherapy. Cardiac irradiations were performed in a single fraction using a TrueBeam linear accelerator (Varian Medical Systems). Results: The delivered dose (mean ± standard deviation) to heart was 1.8±0.2 Gy. Reductions in myocardial stress perfusion relative to baseline were observed in 2 of the 5 animals 1 month post radiation. A global inflammatory response 1 month post radiation was observed in 4 of the 5 animals. The calculated SUV at 1 month post radiation was significantly higher (p=0.05) than the baseline SUV. Conclusion: Low doses of cardiac irradiation (< 2 Gy) may lead to myocardial perfusion defects and a global inflammatory response that can be detectable as early as 1 month post irradiation

[The hybrid operating room. Home of high-end intraoperative imaging].

Science.gov (United States)

Gebhard, F; Riepl, C; Richter, P; Liebold, A; Gorki, H; Wirtz, R; König, R; Wilde, F; Schramm, A; Kraus, M

2012-02-01

A hybrid operating room must serve the medical needs of different highly specialized disciplines. It integrates interventional techniques for cardiovascular procedures and allows operations in the field of orthopaedic surgery, neurosurgery and maxillofacial surgery. The integration of all steps such as planning, documentation and the procedure itself saves time and precious resources. The best available imaging devices and user interfaces reduce the need for extensive personnel in the OR and facilitate new minimally invasive procedures. The immediate possibility of postoperative control images in CT-like quality enables the surgeon to react to problems during the same procedure without the need for later revision.

2D dose distribution images of a hybrid low field MRI-γ detector

Energy Technology Data Exchange (ETDEWEB)

Abril, A., E-mail: ajabrilf@unal.edu.co; Agulles-Pedrós, L., E-mail: lagullesp@unal.edu.co [Medical Physics Group, Physics department, Universidad Nacional de Colombia, Bogotá (Colombia)

2016-07-07

The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the {sup 99m}Tc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.

2D dose distribution images of a hybrid low field MRI-γ detector

International Nuclear Information System (INIS)

Abril, A.; Agulles-Pedrós, L.

2016-01-01

The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the "9"9"mTc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.

2D dose distribution images of a hybrid low field MRI-γ detector

Science.gov (United States)

Abril, A.; Agulles-Pedrós, L.

2016-07-01

The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the 99mTc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.

Synthesis and assessment methods for an edge-alignment-free hybrid image

Science.gov (United States)

Sripian, Peeraya; Yamaguchi, Yasushi

2017-07-01

A hybrid image allows multiple image interpretations to be modulated by the viewing distance. It can be constructed on the basis of the multiscale perceptual mechanisms of the human visual system by combining the low and high spatial frequencies of two different images. The hybrid image was introduced as an experimental tool for visual recognition study in terms of spatial frequency perception. To produce a compelling hybrid image, the original hybrid image synthesis method could only use similar shapes of source images that were aligned in the edges. If any two different images can be hybrid, it would be beneficial as a new experimental tool. In addition, there is no measure for the actual perception of spatial frequency, whether a single spatial frequency or both spatial frequencies are perceived from the hybrid stimulus. This paper describes two methods for synthesizing a hybrid image from dissimilar shape images or unaligned images; this hybrid image is known as an "edge-alignment-free hybrid image." A noise-inserted method can be done by intentionally inserting and enhancing noises into the high-frequency image. With this method, the low-frequency blobs are covered with high-frequency noises when viewed up close. A color-inserted method uses complementary color gratings in the background of the high-frequency image to emphasize the high-frequency image when viewed up close, whereas the gratings disappear when viewed from far away. To ascertain that our approach successfully separates the spatial frequency at each viewing distance, we measured this property using our proposed assessment method. Our proposed method allows the experimenter to quantify the probability of perceiving both spatial frequencies and a single spatial frequency in a hybrid image. The experimental results confirmed that our proposed synthesis methods successfully hid the low-frequency image and emphasized the high-frequency image at a close viewing distance. At the same time, the

Capacitive micromachined ultrasonic transducers for medical imaging and therapy

International Nuclear Information System (INIS)

Khuri-Yakub, Butrus T; Oralkan, Ömer

2011-01-01

Capacitive micromachined ultrasonic transducers (CMUTs) have been subject to extensive research for the last two decades. Although they were initially developed for air-coupled applications, today their main application space is medical imaging and therapy. This paper first presents a brief description of CMUTs, their basic structure and operating principles. Our progression of developing several generations of fabrication processes is discussed with an emphasis on the advantages and disadvantages of each process. Monolithic and hybrid approaches for integrating CMUTs with supporting integrated circuits are surveyed. Several prototype transducer arrays with integrated front-end electronic circuits we developed and their use for 2D and 3D, anatomical and functional imaging, and ablative therapies are described. The presented results prove the CMUT as a micro-electro-mechanical systems technology for many medical diagnostic and therapeutic applications

Capacitive micromachined ultrasonic transducers for medical imaging and therapy.

Science.gov (United States)

Khuri-Yakub, Butrus T; Oralkan, Omer

2011-05-01

Capacitive micromachined ultrasonic transducers (CMUTs) have been subject to extensive research for the last two decades. Although they were initially developed for air-coupled applications, today their main application space is medical imaging and therapy. This paper first presents a brief description of CMUTs, their basic structure, and operating principles. Our progression of developing several generations of fabrication processes is discussed with an emphasis on the advantages and disadvantages of each process. Monolithic and hybrid approaches for integrating CMUTs with supporting integrated circuits are surveyed. Several prototype transducer arrays with integrated frontend electronic circuits we developed and their use for 2-D and 3-D, anatomical and functional imaging, and ablative therapies are described. The presented results prove the CMUT as a MEMS technology for many medical diagnostic and therapeutic applications.

Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization.

Science.gov (United States)

Abdel-Basset, Mohamed; Fakhry, Ahmed E; El-Henawy, Ibrahim; Qiu, Tie; Sangaiah, Arun Kumar

2017-11-03

Image registration is an important aspect in medical image analysis, and kinds use in a variety of medical applications. Examples include diagnosis, pre/post surgery guidance, comparing/merging/integrating images from multi-modal like Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). Whether registering images across modalities for a single patient or registering across patients for a single modality, registration is an effective way to combine information from different images into a normalized frame for reference. Registered datasets can be used for providing information relating to the structure, function, and pathology of the organ or individual being imaged. In this paper a hybrid approach for medical images registration has been developed. It employs a modified Mutual Information (MI) as a similarity metric and Particle Swarm Optimization (PSO) method. Computation of mutual information is modified using a weighted linear combination of image intensity and image gradient vector flow (GVF) intensity. In this manner, statistical as well as spatial image information is included into the image registration process. Maximization of the modified mutual information is effected using the versatile Particle Swarm Optimization which is developed easily with adjusted less parameter. The developed approach has been tested and verified successfully on a number of medical image data sets that include images with missing parts, noise contamination, and/or of different modalities (CT, MRI). The registration results indicate the proposed model as accurate and effective, and show the posture contribution in inclusion of both statistical and spatial image data to the developed approach.

Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

Science.gov (United States)

Awumah, Anna; Mahanti, Prasun; Robinson, Mark

2016-10-01

Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

Elastography as a hybrid imaging technique : coupling with photoacoustics and quantitative imaging

International Nuclear Information System (INIS)

Widlak, T.G.

2015-01-01

While classical imaging methods, such as ultrasound, computed tomography or magnetic resonance imaging, are well-known and mathematically understood, a host of physiological parameters relevant for diagnostic purposes cannot be obtained by them. This gap is recently being closed by the introduction of hybrid, or coupled-physics imaging methods. They connect more then one physical modality, and aim to provide quantitative information on optical, electrical or mechanical parameters with high resolution. Central to this thesis is the mechanical contrast of elastic tissue, especially Young’s modulus or the shear modulus. Different methods of qualitative elastography provide interior information of the mechanical displacement field. From this interior data the nonlinear inverse problem of quantitative elastography aims to reconstruct the shear modulus. In this thesis, the elastography problem is seen from a hybrid imaging perspective; methods from coupled-physics inspired literature and regularization theory have been employed to recover displacement and shear modulus information. The overdetermined systems approach by G. Bal is applied to the quantitative problem, and ellipticity criteria are deduced, for one and several measurements, as well as injectivity results. Together with the geometric theory of G. Chavent, the results are used for analyzing convergence of Tikhonov regularization. Also, a convergence analysis for the Levenberg Marquardt method is provided. As a second mainstream project in this thesis, elastography imaging is developed for extracting displacements from photoacoustic images. A novel method is provided for texturizing the images, and the optical flow problem for motion estimation is shown to be regularized with this texture generation. The results are tested in cooperation with the Medical University Vienna, and the methods for quantitative determination of the shear modulus evaluated in first experiments. In summary, the overdetermined systems

Hybrid imaging, PET-CT and SPECT-CT: What impact on nuclear medicine education and practice in France?

International Nuclear Information System (INIS)

Mundler, O.

2009-01-01

To define the policy of our specialty with a consensus opinion, a questionnaire entitled 'hybrid imaging' was sent to practicing nuclear medicine specialist physicians in France to obtain their opinion on the impact of this recent method in training and in the practice of nuclear medicine and on the relations between nuclear medicine specialists and other medical imaging specialists. This questionnaire, written by the office of the French Society of Nuclear Medicine (F.S.N.M.) and molecular imaging, was divided into four parts: Profile and experience in hybrid imaging, Relations with radiologists, Practice of CT scans with hybrid equipment, and the Future of the specialty and of training in nuclear medicine. The response rate was 60%, i.e. 374 completed questionnaires. Overall, the responses were uniform, whatever the respondent's experience, type and place of practice. Regular participation in hybrid imaging practice was the reply provided by the majority of respondents. In terms of relations with radiologists, such contacts existed in over 85% of cases and are considered as being of high quality in over 90% of cases. The vast majority of practitioners believe that hybrid imaging will become the standard. Opinions on the diagnostic use of CT scans are divided, as well as their interpretation by a radiologist, a nuclear medicine specialist or by both. In the opinion of the vast majority, hybrid equipment systems should be managed by nuclear medicine specialists. With regard to the future, nuclear medicine should remain an independent specialty with enhanced training in morphological imaging and a residency training program whose length should be increased to 5 years. (author)

Hybrid SPECT/CT imaging in neurology.

Science.gov (United States)

Ciarmiello, Andrea; Giovannini, Elisabetta; Meniconi, Martina; Cuccurullo, Vincenzo; Gaeta, Maria Chiara

2014-01-01

In recent years, the SPECT/CT hybrid modality has led to a rapid development of imaging techniques in nuclear medicine, opening new perspectives for imaging staff and patients as well. However, while, the clinical role of positron emission tomography-computed tomography (PET-CT) is well consolidated, the diffusion and the consequent value of single-photon emission tomography-computed tomography (SPECT-CT) has yet to be weighed, Hence, there is a need for a careful analysis, comparing the "potential" benefits of the hybrid modality with the "established" ones of the standalone machine. The aim of this article is to analyze the impact of this hybrid tool on the diagnosis of diseases of the central nervous system, comparing strengths and weaknesses of both modalities through the use of SWOT analysis.

X-ray Imaging Using a Hybrid Photon Counting GaAs Pixel Detector

CERN Document Server

Schwarz, C; Göppert, R; Heijne, Erik H M; Ludwig, J; Meddeler, G; Mikulec, B; Pernigotti, E; Rogalla, M; Runge, K; Smith, K M; Snoeys, W; Söldner-Rembold, S; Watt, J

1999-01-01

The performance of hybrid GaAs pixel detectors as X-ray imaging sensors were investigated at room temperature. These hybrids consist of 300 mu-m thick GaAs pixel detectors, flip-chip bonded to a CMOS Single Photon Counting Chip (PCC). This chip consists of a matrix of 64 x 64 identical square pixels (170 mu-m x 170 mu-m) and covers a total area of 1.2 cm**2. The electronics in each cell comprises a preamplifier, a discriminator with a 3-bit threshold adjust and a 15-bit counter. The detector is realized by an array of Schottky diodes processed on semi-insulating LEC-GaAs bulk material. An IV-charcteristic and a detector bias voltage scan showed that the detector can be operated with voltages around 200 V. Images of various objects were taken by using a standard X-ray tube for dental diagnostics. The signal to noise ratio (SNR) was also determined. The applications of these imaging systems range from medical applications like digital mammography or dental X-ray diagnostics to non destructive material testing (...

Medical ultrasound imaging

DEFF Research Database (Denmark)

Jensen, Jørgen Arendt

2007-01-01

The paper gives an introduction to current medical ultrasound imaging systems. The basics of anatomic and blood flow imaging are described. The properties of medical ultrasound and its focusing are described, and the various methods for two- and three-dimensional imaging of the human anatomy...

Medical image registration for analysis

International Nuclear Information System (INIS)

Petrovic, V.

2006-01-01

Full text: Image registration techniques represent a rich family of image processing and analysis tools that aim to provide spatial correspondences across sets of medical images of similar and disparate anatomies and modalities. Image registration is a fundamental and usually the first step in medical image analysis and this paper presents a number of advanced techniques as well as demonstrates some of the advanced medical image analysis techniques they make possible. A number of both rigid and non-rigid medical image alignment algorithms of equivalent and merely consistent anatomical structures respectively are presented. The algorithms are compared in terms of their practical aims, inputs, computational complexity and level of operator (e.g. diagnostician) interaction. In particular, the focus of the methods discussion is placed on the applications and practical benefits of medical image registration. Results of medical image registration on a number of different imaging modalities and anatomies are presented demonstrating the accuracy and robustness of their application. Medical image registration is quickly becoming ubiquitous in medical imaging departments with the results of such algorithms increasingly used in complex medical image analysis and diagnostics. This paper aims to demonstrate at least part of the reason why

Mapping the different methods adopted for diagnostic imaging instruction at medical schools in Brazil.

Science.gov (United States)

Chojniak, Rubens; Carneiro, Dominique Piacenti; Moterani, Gustavo Simonetto Peres; Duarte, Ivone da Silva; Bitencourt, Almir Galvão Vieira; Muglia, Valdair Francisco; D'Ippolito, Giuseppe

2017-01-01

To map the different methods for diagnostic imaging instruction at medical schools in Brazil. In this cross-sectional study, a questionnaire was sent to each of the coordinators of 178 Brazilian medical schools. The following characteristics were assessed: teaching model; total course hours; infrastructure; numbers of students and professionals involved; themes addressed; diagnostic imaging modalities covered; and education policies related to diagnostic imaging. Of the 178 questionnaires sent, 45 (25.3%) were completed and returned. Of those 45 responses, 17 (37.8%) were from public medical schools, whereas 28 (62.2%) were from private medical schools. Among the 45 medical schools evaluated, the method of diagnostic imaging instruction was modular at 21 (46.7%), classic (independent discipline) at 13 (28.9%), hybrid (classical and modular) at 9 (20.0%), and none of the preceding at 3 (6.7%). Diagnostic imaging is part of the formal curriculum at 36 (80.0%) of the schools, an elective course at 3 (6.7%), and included within another modality at 6 (13.3%). Professors involved in diagnostic imaging teaching are radiologists at 43 (95.5%) of the institutions. The survey showed that medical courses in Brazil tend to offer diagnostic imaging instruction in courses that include other content and at different time points during the course. Radiologists are extensively involved in undergraduate medical education, regardless of the teaching methodology employed at the institution.

Medical Imaging System

Science.gov (United States)

1991-01-01

The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.

Frontiers in medical imaging technology

International Nuclear Information System (INIS)

Iinuma, Takeshi

1992-01-01

At present many medical images are used for diagnostics and treatment. After the advent of X-ray computer tomography (XCT), the violent development of medical images has continued. Medical imaging technology can be defined as the field of technology that deals with the production, processing, display, transmission, evaluation and so on of medical images, and it can be said that the present development of medical imaging diagnostics has been led by medical imaging technology. In this report, the most advanced technology of medical imaging is explained. The principle of XCT is shown. The feature of XCT is that it can image the delicate difference in the X-ray absorption factor of the cross section being measured. The technical development has been advanced to reduce the time for imaging and to heighten the resolution. The technology which brings about a large impact to future imaging diagnostics is computed radiography. Magnetic resonance imaging is the method of imaging the distribution of protons in human bodies. Positron CT is the method of measurement by injecting a positron-emitting RI. These methods are explained. (K.I.)

Machine learning and medical imaging

CERN Document Server

Shen, Dinggang; Sabuncu, Mert

2016-01-01

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, a...

Digital medical imaging

International Nuclear Information System (INIS)

Goeringer, F.; Mun, S.K.; Kerlin, B.D.

1989-01-01

In formulating an implementation strategy for digital medical imaging, three interrelated thrusts have emerged for the defense medical establishment. These thrusts: totally filmless medical imaging on the battlefield, teleradiology, and DIN/PACS for peacetime military health care are discussed. They have implications in their fully developed form as resource savers and quality improvers for the unique aspects of military health care

Role of CT in hybrid imaging. Point of view of the medical physicist

International Nuclear Information System (INIS)

Gardin, I.; Hapdey, S.

2010-01-01

The recent introduction of hybrid systems SPECT/CT and PET/CT in nuclear medicine, greatly improved the diagnostic accuracy for particular clinical indications, due to the possible attenuation correction of functional images and the availability of helpful anatomic information. The introduction of CT in the nuclear diagnostic process results in a significant increase of the patient dose. This increase should be justified and optimized considering both the clinical question and the CT settings available on these systems. The choice of CT settings directly affects the effective dose. It varies basically as the square of the tube voltage, linearly with the length of the scan and the product of the current by the rotation time of the tube. It is also inversely proportional to the pitch. For attenuation correction, the literature shows that it is possible to use a low CT tube current without significant effect on tumor FDG uptake or lesion size. Conversely low CT voltage must be used with caution, depending on the algorithm implemented in the CT hybrid device to transform CT Hounsfield units to the attenuation map at the appropriate energy. The radiation dose for anatomic correlation can be substantially lower than for diagnostic-quality CT. It is possible to reduce the patient's radiation dose by a factor of 2 or 3 by acquiring a low-dose PET/CT scan for anatomic correlation of adequate image quality if compared with diagnostic 18 FDG PET/CT. Using specific CT settings, the effective dose can range 7.3-11.3 mSv depending on the patient weight and age. (authors)

Advances in medical image computing.

Science.gov (United States)

Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

2009-01-01

Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Hybrid Simulation in Teaching Clinical Breast Examination to Medical Students.

Science.gov (United States)

Nassif, Joseph; Sleiman, Abdul-Karim; Nassar, Anwar H; Naamani, Sima; Sharara-Chami, Rana

2017-10-10

Clinical breast examination (CBE) is traditionally taught to third-year medical students using a lecture and a tabletop breast model. The opportunity to clinically practice CBE depends on patient availability and willingness to be examined by students, especially in culturally sensitive environments. We propose the use of a hybrid simulation model consisting of a standardized patient (SP) wearing a silicone breast simulator jacket and hypothesize that this, compared to traditional teaching methods, would result in improved learning. Consenting third-year medical students (N = 82) at a university-affiliated tertiary care center were cluster-randomized into two groups: hybrid simulation (breast jacket + SP) and control (tabletop breast model). Students received the standard lecture by instructors blinded to the randomization, followed by randomization group-based learning and practice sessions. Two weeks later, participants were assessed in an Objective Structured Clinical Examination (OSCE), which included three stations with SPs blinded to the intervention. The SPs graded the students on CBE completeness, and students completed a self-assessment of their performance and confidence during the examination. CBE completeness scores did not differ between the two groups (p = 0.889). Hybrid simulation improved lesion identification grades (p simulation relieved the fear of missing a lesion on CBE (p = 0.043) and increased satisfaction with the teaching method among students (p = 0.002). As a novel educational tool, hybrid simulation improves the sensitivity of CBE performed by medical students without affecting its specificity. Hybrid simulation may play a role in increasing the confidence of medical students during CBE.

Medical Imaging.

Science.gov (United States)

Barker, M. C. J.

1996-01-01

Discusses four main types of medical imaging (x-ray, radionuclide, ultrasound, and magnetic resonance) and considers their relative merits. Describes important recent and possible future developments in image processing. (Author/MKR)

Medical Image Tamper Detection Based on Passive Image Authentication.

Science.gov (United States)

Ulutas, Guzin; Ustubioglu, Arda; Ustubioglu, Beste; V Nabiyev, Vasif; Ulutas, Mustafa

2017-12-01

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

Recent Development of Dual-Dictionary Learning Approach in Medical Image Analysis and Reconstruction.

Science.gov (United States)

Wang, Bigong; Li, Liang

2015-01-01

As an implementation of compressive sensing (CS), dual-dictionary learning (DDL) method provides an ideal access to restore signals of two related dictionaries and sparse representation. It has been proven that this method performs well in medical image reconstruction with highly undersampled data, especially for multimodality imaging like CT-MRI hybrid reconstruction. Because of its outstanding strength, short signal acquisition time, and low radiation dose, DDL has allured a broad interest in both academic and industrial fields. Here in this review article, we summarize DDL's development history, conclude the latest advance, and also discuss its role in the future directions and potential applications in medical imaging. Meanwhile, this paper points out that DDL is still in the initial stage, and it is necessary to make further studies to improve this method, especially in dictionary training.

Hybrid wavefront sensing and image correction algorithm for imaging through turbulent media

Science.gov (United States)

Wu, Chensheng; Robertson Rzasa, John; Ko, Jonathan; Davis, Christopher C.

2017-09-01

It is well known that passive image correction of turbulence distortions often involves using geometry-dependent deconvolution algorithms. On the other hand, active imaging techniques using adaptive optic correction should use the distorted wavefront information for guidance. Our work shows that a hybrid hardware-software approach is possible to obtain accurate and highly detailed images through turbulent media. The processing algorithm also takes much fewer iteration steps in comparison with conventional image processing algorithms. In our proposed approach, a plenoptic sensor is used as a wavefront sensor to guide post-stage image correction on a high-definition zoomable camera. Conversely, we show that given the ground truth of the highly detailed image and the plenoptic imaging result, we can generate an accurate prediction of the blurred image on a traditional zoomable camera. Similarly, the ground truth combined with the blurred image from the zoomable camera would provide the wavefront conditions. In application, our hybrid approach can be used as an effective way to conduct object recognition in a turbulent environment where the target has been significantly distorted or is even unrecognizable.

Intelligent distributed medical image management

Science.gov (United States)

Garcia, Hong-Mei C.; Yun, David Y.

1995-05-01

The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

Recent progress in medical imaging technology

International Nuclear Information System (INIS)

Endo, Masahiro

2004-01-01

Medical imaging is name of methods for diagnosis and therapy, which make visible with physical media such as X-ray, structures and functions of man's inside those are usually invisible. These methods are classified by the physical media into ultrasound imaging, magnetic resonance imaging, nuclear medicine imaging and X-ray imaging etc. Having characteristics different from one another, these are used complementarily in medical fields though in some case being competitive. Medical imaging is supported by highly progressed technology, which is called medical imaging technology. This paper describes a survey of recent progress of medical imaging technology in magnetic resonance imaging, nuclear medicine imaging and X-ray imaging. (author)

Roles of medical image processing in medical physics

International Nuclear Information System (INIS)

Arimura, Hidetaka

2011-01-01

Image processing techniques including pattern recognition techniques play important roles in high precision diagnosis and radiation therapy. The author reviews a symposium on medical image information, which was held in the 100th Memorial Annual Meeting of the Japan Society of Medical Physics from September 23rd to 25th. In this symposium, we had three invited speakers, Dr. Akinobu Shimizu, Dr. Hideaki Haneishi, and Dr. Hirohito Mekata, who are active engineering researchers of segmentation, image registration, and pattern recognition, respectively. In this paper, the author reviews the roles of the medical imaging processing in medical physics field, and the talks of the three invited speakers. (author)

Medical imaging

International Nuclear Information System (INIS)

Elliott, Alex

2005-01-01

Diagnostic medical imaging is a fundamental part of the practice of modern medicine and is responsible for the expenditure of considerable amounts of capital and revenue monies in healthcare systems around the world. Much research and development work is carried out, both by commercial companies and the academic community. This paper reviews briefly each of the major diagnostic medical imaging techniques-X-ray (planar and CT), ultrasound, nuclear medicine (planar, SPECT and PET) and magnetic resonance. The technical challenges facing each are highlighted, with some of the most recent developments. In terms of the future, interventional/peri-operative imaging, the advancement of molecular medicine and gene therapy are identified as potential areas of expansion

Medical imaging

CERN Document Server

Townsend, David W

1996-01-01

Since the introduction of the X-ray scanner into radiology almost 25 years ago, non-invasive imaging has become firmly established as an essential tool in the diagnosis of disease. Fully three-dimensional imaging of internal organs is now possible, b and for studies which explore the functional status of the body. Powerful techniques to correlate anatomy and function are available, and scanners which combine anatomical and functional imaging in a single device are under development. Such techniques have been made possible through r ecent technological and mathematical advances. This series of lectures will review both the physical basis of medical imaging techniques using X-rays, gamma and positron emitting radiosiotopes, and nuclear magnetic resonance, and the mathematical methods used to reconstruct three-dimentional distributions from projection data. The lectures will trace the development of medical imaging from simple radiographs to the present-day non-invasive measurement of in vivo biochemistry. They ...

Recent Development of Dual-Dictionary Learning Approach in Medical Image Analysis and Reconstruction

Science.gov (United States)

Wang, Bigong; Li, Liang

2015-01-01

As an implementation of compressive sensing (CS), dual-dictionary learning (DDL) method provides an ideal access to restore signals of two related dictionaries and sparse representation. It has been proven that this method performs well in medical image reconstruction with highly undersampled data, especially for multimodality imaging like CT-MRI hybrid reconstruction. Because of its outstanding strength, short signal acquisition time, and low radiation dose, DDL has allured a broad interest in both academic and industrial fields. Here in this review article, we summarize DDL's development history, conclude the latest advance, and also discuss its role in the future directions and potential applications in medical imaging. Meanwhile, this paper points out that DDL is still in the initial stage, and it is necessary to make further studies to improve this method, especially in dictionary training. PMID:26089956

Development of a PET/Cerenkov-light hybrid imaging system

International Nuclear Information System (INIS)

Yamamoto, Seiichi; Hamamura, Fuka; Kato, Katsuhiko; Ogata, Yoshimune; Watabe, Tadashi; Ikeda, Hayato; Kanai, Yasukazu; Hatazawa, Jun; Watabe, Hiroshi

2014-01-01

Purpose: Cerenkov-light imaging is a new molecular imaging technology that detects visible photons from high-speed electrons using a high sensitivity optical camera. However, the merit of Cerenkov-light imaging remains unclear. If a PET/Cerenkov-light hybrid imaging system were developed, the merit of Cerenkov-light imaging would be clarified by directly comparing these two imaging modalities. Methods: The authors developed and tested a PET/Cerenkov-light hybrid imaging system that consists of a dual-head PET system, a reflection mirror located above the subject, and a high sensitivity charge coupled device (CCD) camera. The authors installed these systems inside a black box for imaging the Cerenkov-light. The dual-head PET system employed a 1.2 × 1.2 × 10 mm 3 GSO arranged in a 33 × 33 matrix that was optically coupled to a position sensitive photomultiplier tube to form a GSO block detector. The authors arranged two GSO block detectors 10 cm apart and positioned the subject between them. The Cerenkov-light above the subject is reflected by the mirror and changes its direction to the side of the PET system and is imaged by the high sensitivity CCD camera. Results: The dual-head PET system had a spatial resolution of ∼1.2 mm FWHM and sensitivity of ∼0.31% at the center of the FOV. The Cerenkov-light imaging system's spatial resolution was ∼275μm for a 22 Na point source. Using the combined PET/Cerenkov-light hybrid imaging system, the authors successfully obtained fused images from simultaneously acquired images. The image distributions are sometimes different due to the light transmission and absorption in the body of the subject in the Cerenkov-light images. In simultaneous imaging of rat, the authors found that 18 F-FDG accumulation was observed mainly in the Harderian gland on the PET image, while the distribution of Cerenkov-light was observed in the eyes. Conclusions: The authors conclude that their developed PET/Cerenkov-light hybrid imaging

An Approach to Management of Health Care and Medical Diagnosis Using of a Hybrid Disease Diagnosis System

Directory of Open Access Journals (Sweden)

Hodjat Hamidi

2017-02-01

Full Text Available Introduction: In order to simplify the information exchange within the medical diagnosis process, a collaborative software agent’s framework is presented. The purpose of the framework is to allow the automated information exchange between different medicine specialists. Methods: This study presented architecture of a hybrid disease diagnosis system. The architecture employed a learning algorithm and used soft computing to build a medical knowledge base. These machine intelligences are combined in a complementary approach to overcome the weakness of each other. To evaluate the hybrid learning algorithm and compare it with other methods, 699 samples were used in each experiment, where 60% was for training, 20% was for cross validation, and 20% for testing. Results: The results were obtained from the experiments on the breast cancer dataset. Different methods of soft computing system were merged to create diagnostic software functionality. As it is shown in the structure, the system has the ability to learn and collect knowledge that can be used in the detection of new images. Currently, the system is at the design stage. The system is to evaluate the performance of hybrid learning algorithm. The preliminary results showed a better performance of this system than other methods. However, the results can be tested with hybrid system on larger data sets to improve hybrid learning algorithm. Conclusion: The purpose of this paper was to simplify the diagnosis process of a patient by splitting the medical domain concepts (e.g., causes, effects, symptoms, tests in human body systems (e.g., respiratory, cardiovascular, though maintaining the holistic perspective through the links between common concepts.

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

Science.gov (United States)

al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

2015-12-01

This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

Image processing in medical ultrasound

DEFF Research Database (Denmark)

Hemmsen, Martin Christian

This Ph.D project addresses image processing in medical ultrasound and seeks to achieve two major scientific goals: First to develop an understanding of the most significant factors influencing image quality in medical ultrasound, and secondly to use this knowledge to develop image processing...... multiple imaging setups. This makes the system well suited for development of new processing methods and for clinical evaluations, where acquisition of the exact same scan location for multiple methods is important. The second project addressed implementation, development and evaluation of SASB using...... methods for enhancing the diagnostic value of medical ultrasound. The project is an industrial Ph.D project co-sponsored by BK Medical ApS., with the commercial goal to improve the image quality of BK Medicals scanners. Currently BK Medical employ a simple conventional delay-and-sum beamformer to generate...

Medical physics 2013. Abstracts

International Nuclear Information System (INIS)

Treuer, Harald

2013-01-01

The proceedings of the medical physics conference 2013 include abstract of lectures and poster sessions concerning the following issues: Tele-therapy - application systems, nuclear medicine and molecular imaging, neuromodulation, hearing and technical support, basic dosimetry, NMR imaging -CEST (chemical exchange saturation transfer), medical robotics, magnetic particle imaging, audiology, radiation protection, phase contrast - innovative concepts, particle therapy, brachytherapy, computerized tomography, quantity assurance, hybrid imaging techniques, diffusion and lung NMR imaging, image processing - visualization, cardiac and abdominal NMR imaging.

Structure of the medical digital image

International Nuclear Information System (INIS)

Baltadzhiev, D.

1997-01-01

In up-to-date medical practice diagnostic imaging techniques are the most powerful tools available to clinicians. The modern medical equipment is entirely based on digital technology. In this article the principle of generating medical images is presented. The concept for gray scale where medical images are commonly presented is described. The patterns of gray images transformation into colour scale are likewise outlined. Basic notions from medical imaging terminology such as image matrix, pixel, spatial and contrast resolution power, bit, byte and the like are explained. Also an example is given of how the binary system treats images. On the basis of digital technology the obtained medical images lend themselves readily to additional processing, reconstruction (including 3D) and storage for subsequent utilization. The ceaseless progress of computerized communications promote easy and prompt access for clinicians to the diagnostic images needed as well as realization of expert consultations by teleconference contact (author)

Response of a hybrid pixel detector (MEDIPIX3) to different radiation sources for medical applications

Energy Technology Data Exchange (ETDEWEB)

Chumacero, E. Miguel; De Celis Alonso, B.; Martínez Hernández, M. I.; Vargas, G.; Moreno Barbosa, E., E-mail: emoreno.emb@gmail.com [Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Av. San Claudio y Rio Verde, Puebla (Mexico); Moreno Barbosa, F. [Hospital General del Sur Hospital de la Mujer, Puebla (Mexico)

2014-11-07

The development in semiconductor CMOS technology has enabled the creation of sensitive detectors for a wide range of ionizing radiation. These devices are suitable for photon counting and can be used in imaging and tomography X-ray diagnostics. The Medipix[1] radiation detection system is a hybrid silicon pixel chip developed for particle tracking applications in High Energy Physics. Its exceptional features (high spatial and energy resolution, embedded ultra fast readout, different operation modes, etc.) make the Medipix an attractive device for applications in medical imaging. In this work the energy characterization of a third-generation Medipix chip (Medipix3) coupled to a silicon sensor is presented. We used different radiation sources (strontium 90, iron 55 and americium 241) to obtain the response curve of the hybrid detector as a function of energy. We also studied the contrast of the Medipix as a measure of pixel noise. Finally we studied the response to fluorescence X rays from different target materials (In, Pd and Cd) for the two data acquisition modes of the chip; single pixel mode and charge summing mode.

Processing of medical images

International Nuclear Information System (INIS)

Restrepo, A.

1998-01-01

Thanks to the innovations in the technology for the processing of medical images, to the high development of better and cheaper computers, and, additionally, to the advances in the systems of communications of medical images, the acquisition, storage and handling of digital images has acquired great importance in all the branches of the medicine. It is sought in this article to introduce some fundamental ideas of prosecution of digital images that include such aspects as their representation, storage, improvement, visualization and understanding

Primary gamma ray selection in a hybrid timing/imaging Cherenkov array

Directory of Open Access Journals (Sweden)

Postnikov E.B.

2017-01-01

Full Text Available This work is a methodical study on hybrid reconstruction techniques for hybrid imaging/timing Cherenkov observations. This type of hybrid array is to be realized at the gamma-observatory TAIGA intended for very high energy gamma-ray astronomy (> 30 TeV. It aims at combining the cost-effective timing-array technique with imaging telescopes. Hybrid operation of both of these techniques can lead to a relatively cheap way of development of a large area array. The joint approach of gamma event selection was investigated on both types of simulated data: the image parameters from the telescopes, and the shower parameters reconstructed from the timing array. The optimal set of imaging parameters and shower parameters to be combined is revealed. The cosmic ray background suppression factor depending on distance and energy is calculated. The optimal selection technique leads to cosmic ray background suppression of about 2 orders of magnitude on distances up to 450 m for energies greater than 50 TeV.

A Hybrid Technique for De-Noising Multi-Modality Medical Images by Employing Cuckoo’s Search with Curvelet Transform

Directory of Open Access Journals (Sweden)

Qaisar Javaid

2018-01-01

Full Text Available De-noising of the medical images is very difficult task. To improve the overall visual representation we need to apply a contrast enhancement techniques, this representation provide the physicians and clinicians a good and recovered diagnosis results. Various de-noising and contrast enhancements methods are develops. However, some of the methods are not good in providing the better results with accuracy and efficiency. In our paper we de-noise and enhance the medical images without any loss of information. We uses the curvelet transform in combination with ridglet transform along with CS (Cuckoo Search algorithm. The curvlet transform adapt and represents the sparse pixel informations with all edges. The edges play very important role in understanding of the images. Curvlet transform computes the edges very efficiently where the wavelets are failed. We used the CS to optimize the de-noising coefficients without loss of structural and morphological information. Our designed method would be accurate and efficient in de-noising the medical images. Our method attempts to remove the multiplicative and additive noises. Our proposed method is proved to be an efficient and reliable in removing all kind of noises from the medical images. Result indicates that our proposed approach is better than other approaches in removing impulse, Gaussian, and speckle noises.

Hiding Electronic Patient Record (EPR) in medical images: A high capacity and computationally efficient technique for e-healthcare applications.

Science.gov (United States)

Loan, Nazir A; Parah, Shabir A; Sheikh, Javaid A; Akhoon, Jahangir A; Bhat, Ghulam M

2017-09-01

A high capacity and semi-reversible data hiding scheme based on Pixel Repetition Method (PRM) and hybrid edge detection for scalable medical images has been proposed in this paper. PRM has been used to scale up the small sized image (seed image) and hybrid edge detection ensures that no important edge information is missed. The scaled up version of seed image has been divided into 2×2 non overlapping blocks. In each block there is one seed pixel whose status decides the number of bits to be embedded in the remaining three pixels of that block. The Electronic Patient Record (EPR)/data have been embedded by using Least Significant and Intermediate Significant Bit Substitution (ISBS). The RC4 encryption has been used to add an additional security layer for embedded EPR/data. The proposed scheme has been tested for various medical and general images and compared with some state of art techniques in the field. The experimental results reveal that the proposed scheme besides being semi-reversible and computationally efficient is capable of handling high payload and as such can be used effectively for electronic healthcare applications. Copyright © 2017. Published by Elsevier Inc.

A study on the optimization of referring method about medical images using MIH (Medical Image History)

International Nuclear Information System (INIS)

Kim, Sun Chil; Kim, Jung Min

2002-01-01

The recent development of embodiment technology of the medical images makes most medical institutions introduce PACS (Picture Archiving and Communication System) in haste. However lots of PACS solutions, currently developed and distributed, haven't been able to serve the convenience of users and to satisfy user's demand because of economic limitations and administrator-oriented con-siderations in the process of development. So we have developed MIH (Medical Image History), by which we can search and refer to the patient's medical images and information with few restrictions of time and space for diagnosis and treatment. The program will contribute to the improvement in the medical environment and meet the clients' need. We'll make more effort to develop the application which insures the better quality of medical images. MIH manages the patient's image files and medical records like film chart in connection with time. This trial will contribute to the reduction of the economical loss caused by unnecessary references and improve the quality in the medical services. The demand on the development of the program which refers to the medical data quickly and keeps them stable will be continued by the medical institute. This will satisfy the client's demand and improve the service to the patients in that the program will be modified from the standpoint of the users. MIH is trying to keep user-oriented policy and to apply the benefit of the analog system to the digital environment. It is necessary to lead the public to the better understanding that the systematic management and referring of the medical images is as important as the quality of the images

A Hybrid Method for Image Segmentation Based on Artificial Fish Swarm Algorithm and Fuzzy c-Means Clustering

Directory of Open Access Journals (Sweden)

Li Ma

2015-01-01

Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM clustering is one of the popular clustering algorithms for medical image segmentation. However, FCM has the problems of depending on initial clustering centers, falling into local optimal solution easily, and sensitivity to noise disturbance. To solve these problems, this paper proposes a hybrid artificial fish swarm algorithm (HAFSA. The proposed algorithm combines artificial fish swarm algorithm (AFSA with FCM whose advantages of global optimization searching and parallel computing ability of AFSA are utilized to find a superior result. Meanwhile, Metropolis criterion and noise reduction mechanism are introduced to AFSA for enhancing the convergence rate and antinoise ability. The artificial grid graph and Magnetic Resonance Imaging (MRI are used in the experiments, and the experimental results show that the proposed algorithm has stronger antinoise ability and higher precision. A number of evaluation indicators also demonstrate that the effect of HAFSA is more excellent than FCM and suppressed FCM (SFCM.

Noise analysis of a novel hybrid active-passive pixel sensor for medical X-ray imaging

International Nuclear Information System (INIS)

Safavian, N.; Izadi, M.H.; Sultana, A.; Wu, D.; Karim, K.S.; Nathan, A.; Rowlands, J.A.

2009-01-01

Passive pixel sensor (PPS) is one of the most widely used architectures in large area amorphous silicon (a-Si) flat panel imagers. It consists of a detector and a thin film transistor (TFT) acting as a readout switch. While the PPS is advantageous in terms of providing a simple and small architecture suitable for high-resolution imaging, it directly exposes the signal to the noise of data line and external readout electronics, causing significant increase in the minimum readable sensor input signal. In this work we present the operation and noise performance of a hybrid 3-TFT current programmed, current output active pixel sensor (APS) suitable for real-time X-ray imaging. The pixel circuit extends the application of a-Si TFT from conventional switching element to on-pixel amplifier for enhanced signal-to-noise ratio and higher imager dynamic range. The capability of operation in both passive and active modes as well as being able to compensate for inherent instabilities of the TFTs makes the architecture a good candidate for X-ray imaging modalities with a wide range of incoming X-ray intensities. Measurement and theoretical calculations reveal a value for input refferd noise below the 1000 electron noise limit for real-time fluoroscopy. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Luminescence in medical image science

Energy Technology Data Exchange (ETDEWEB)

Kandarakis, I.S., E-mail: kandarakis@teiath.gr

2016-01-15

Radiation detection in Medical Imaging is mostly based on the use of luminescent materials (scintillators and phosphors) coupled to optical sensors. Materials are employed in the form of granular screens, structured (needle-like) crystals and single crystal transparent blocks. Storage phosphors are also incorporated in some x-ray imaging plates. Description of detector performance is currently based on quality metrics, such as the Luminescence efficiency, the Modulation Transfer Function (MTF), the Noise Power Spectrum (NPS) and the Detective Quantum Efficiency (DQE) can be defined and evaluated. The aforementioned metrics are experimental evaluated for various materials in the form of screens. A software was designed (MINORE v1) to present image quality measurements in a graphical user interface (GUI) environment. Luminescence efficiency, signal and noise analysis are valuable tools for the evaluation of luminescent materials as candidates for medical imaging detectors. - Highlights: • Luminescence based medical imaging detectors. • Image science: MTF, NPS, DQE. • Phosphors screens light emission efficiency experimental evaluation. • Theoretical models for estimation of phosphor screen properties. • Software for medical image quality metrics.

A study on the optimization of referring method about medical images using MIH (Medical Image History)

Energy Technology Data Exchange (ETDEWEB)

Kim, Sun Chil; Kim, Jung Min [College of Health Sciences, Korea University, Seoul (Korea, Republic of)

2002-09-15

The recent development of embodiment technology of the medical images makes most medical institutions introduce PACS (Picture Archiving and Communication System) in haste. However lots of PACS solutions, currently developed and distributed, haven't been able to serve the convenience of users and to satisfy user's demand because of economic limitations and administrator-oriented con-siderations in the process of development. So we have developed MIH (Medical Image History), by which we can search and refer to the patient's medical images and information with few restrictions of time and space for diagnosis and treatment. The program will contribute to the improvement in the medical environment and meet the clients' need. We'll make more effort to develop the application which insures the better quality of medical images. MIH manages the patient's image files and medical records like film chart in connection with time. This trial will contribute to the reduction of the economical loss caused by unnecessary references and improve the quality in the medical services. The demand on the development of the program which refers to the medical data quickly and keeps them stable will be continued by the medical institute. This will satisfy the client's demand and improve the service to the patients in that the program will be modified from the standpoint of the users. MIH is trying to keep user-oriented policy and to apply the benefit of the analog system to the digital environment. It is necessary to lead the public to the better understanding that the systematic management and referring of the medical images is as important as the quality of the images.

Medical imaging

International Nuclear Information System (INIS)

Loshkajian, A.

2000-01-01

This didactical book presents the medical imaging techniques: radiography, scanner, nuclear magnetic resonance (NMR). Examples are given for the most common pathologies in all domains of medicine. (J.S.)

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.

Java advanced medical image toolkit

International Nuclear Information System (INIS)

Saunder, T.H.C.; O'Keefe, G.J.; Scott, A.M.

2002-01-01

Full text: The Java Advanced Medical Image Toolkit (jAMIT) has been developed at the Center for PET and Department of Nuclear Medicine in an effort to provide a suite of tools that can be utilised in applications required to perform analysis, processing and visualisation of medical images. jAMIT uses Java Advanced Imaging (JAI) to combine the platform independent nature of Java with the speed benefits associated with native code. The object-orientated nature of Java allows the production of an extensible and robust package which is easily maintained. In addition to jAMIT, a Medical Image VO API called Sushi has been developed to provide access to many commonly used image formats. These include DICOM, Analyze, MINC/NetCDF, Trionix, Beat 6.4, Interfile 3.2/3.3 and Odyssey. This allows jAMIT to access data and study information contained in different medical image formats transparently. Additional formats can be added at any time without any modification to the jAMIT package. Tools available in jAMIT include 2D ROI Analysis, Palette Thresholding, Image Groping, Image Transposition, Scaling, Maximum Intensity Projection, Image Fusion, Image Annotation and Format Conversion. Future tools may include 2D Linear and Non-linear Registration, PET SUV Calculation, 3D Rendering and 3D ROI Analysis. Applications currently using JAMIT include Antibody Dosimetry Analysis, Mean Hemispheric Blood Flow Analysis, QuickViewing of PET Studies for Clinical Training, Pharamcodynamic Modelling based on Planar Imaging, and Medical Image Format Conversion. The use of jAMIT and Sushi for scripting and analysis in Matlab v6.1 and Jython is currently being explored. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

Development of a hardware-based registration system for the multimodal medical images by USB cameras

International Nuclear Information System (INIS)

Iwata, Michiaki; Minato, Kotaro; Watabe, Hiroshi; Koshino, Kazuhiro; Yamamoto, Akihide; Iida, Hidehiro

2009-01-01

There are several medical imaging scanners and each modality has different aspect for visualizing inside of human body. By combining these images, diagnostic accuracy could be improved, and therefore, several attempts for multimodal image registration have been implemented. One popular approach is to use hybrid image scanners such as positron emission tomography (PET)/CT and single photon emission computed tomography (SPECT)/CT. However, these hybrid scanners are expensive and not fully available. We developed multimodal image registration system with universal serial bus (USB) cameras, which is inexpensive and applicable to any combinations of existed conventional imaging scanners. The multiple USB cameras will determine the three dimensional positions of a patient while scanning. Using information of these positions and rigid body transformation, the acquired image is registered to the common coordinate which is shared with another scanner. For each scanner, reference marker is attached on gantry of the scanner. For observing the reference marker's position by the USB cameras, the location of the USB cameras can be arbitrary. In order to validate the system, we scanned a cardiac phantom with different positions by PET and MRI scanners. Using this system, images from PET and MRI were visually aligned, and good correlations between PET and MRI images were obtained after the registration. The results suggest this system can be inexpensively used for multimodal image registrations. (author)

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.

Medical Imaging Informatics in Nuclear Medicine

NARCIS (Netherlands)

van Ooijen, Peter; Glaudemans, Andor W.J.M.; Medema, Jitze; van Zanten, Annie K.; Dierckx, Rudi A.J.O.; Ahaus, C.T.B. (Kees)

2016-01-01

Medical imaging informatics is gaining importance in medicine both in clinical practice and in scientific research. Besides radiology, nuclear medicine is also a major stakeholder in medical imaging informatics because of the variety of available imaging modalities and the imaging-oriented operation

New hybrid voxelized/analytical primitive in Monte Carlo simulations for medical applications

International Nuclear Information System (INIS)

Bert, Julien; Lemaréchal, Yannick; Visvikis, Dimitris

2016-01-01

Monte Carlo simulations (MCS) applied in particle physics play a key role in medical imaging and particle therapy. In such simulations, particles are transported through voxelized phantoms derived from predominantly patient CT images. However, such voxelized object representation limits the incorporation of fine elements, such as artificial implants from CAD modeling or anatomical and functional details extracted from other imaging modalities. In this work we propose a new hYbrid Voxelized/ANalytical primitive (YVAN) that combines both voxelized and analytical object descriptions within the same MCS, without the need to simultaneously run two parallel simulations, which is the current gold standard methodology. Given that YVAN is simply a new primitive object, it does not require any modifications on the underlying MC navigation code. The new proposed primitive was assessed through a first simple MCS. Results from the YVAN primitive were compared against an MCS using a pure analytical geometry and the layer mass geometry concept. A perfect agreement was found between these simulations, leading to the conclusion that the new hybrid primitive is able to accurately and efficiently handle phantoms defined by a mixture of voxelized and analytical objects. In addition, two application-based evaluation studies in coronary angiography and intra-operative radiotherapy showed that the use of YVAN was 6.5% and 12.2% faster than the layered mass geometry method, respectively, without any associated loss of accuracy. However, the simplification advantages and differences in computational time improvements obtained with YVAN depend on the relative proportion of the analytical and voxelized structures used in the simulation as well as the size and number of triangles used in the description of the analytical object meshes. (paper)

New hybrid voxelized/analytical primitive in Monte Carlo simulations for medical applications.

Science.gov (United States)

Bert, Julien; Lemaréchal, Yannick; Visvikis, Dimitris

2016-05-07

Monte Carlo simulations (MCS) applied in particle physics play a key role in medical imaging and particle therapy. In such simulations, particles are transported through voxelized phantoms derived from predominantly patient CT images. However, such voxelized object representation limits the incorporation of fine elements, such as artificial implants from CAD modeling or anatomical and functional details extracted from other imaging modalities. In this work we propose a new hYbrid Voxelized/ANalytical primitive (YVAN) that combines both voxelized and analytical object descriptions within the same MCS, without the need to simultaneously run two parallel simulations, which is the current gold standard methodology. Given that YVAN is simply a new primitive object, it does not require any modifications on the underlying MC navigation code. The new proposed primitive was assessed through a first simple MCS. Results from the YVAN primitive were compared against an MCS using a pure analytical geometry and the layer mass geometry concept. A perfect agreement was found between these simulations, leading to the conclusion that the new hybrid primitive is able to accurately and efficiently handle phantoms defined by a mixture of voxelized and analytical objects. In addition, two application-based evaluation studies in coronary angiography and intra-operative radiotherapy showed that the use of YVAN was 6.5% and 12.2% faster than the layered mass geometry method, respectively, without any associated loss of accuracy. However, the simplification advantages and differences in computational time improvements obtained with YVAN depend on the relative proportion of the analytical and voxelized structures used in the simulation as well as the size and number of triangles used in the description of the analytical object meshes.

Nuclear imaging in the realm of medical imaging

International Nuclear Information System (INIS)

Deconinck, Frank

2003-01-01

In medical imaging, information concerning the anatomy or biological processes of a patient is detected and presented on film or screen for interpretation by a reader. The information flow from patient to reader optimally implies: - the emission, transmission or reflection of information carriers, typically photons or sound waves, which have to be correctly modulated by patient information through interactions in the patient; - their detection by adequate imaging equipment preserving essential spectral, spatial and/or temporal information; - the presentation of the information in the most perceivable way; - the observation by an unbiased and trained expert. In reality, only an approximation to this optimal situation is achieved. It is the goal of R and D in the medical imaging field to approach the optimum as much as possible within societal constraints such as patient risk and comfort, economics, etc. First, the basic physical concepts underlying the imaging process will be introduced. Different imaging modalities will then be situated in the realm of medical imaging with some emphasis on nuclear imaging

Towards integration of PET/MR hybrid imaging into radiation therapy treatment planning

International Nuclear Information System (INIS)

Paulus, Daniel H.; Thorwath, Daniela; Schmidt, Holger; Quick, Harald H.

2014-01-01

Purpose: Multimodality imaging has become an important adjunct of state-of-the-art radiation therapy (RT) treatment planning. Recently, simultaneous PET/MR hybrid imaging has become clinically available and may also contribute to target volume delineation and biological individualization in RT planning. For integration of PET/MR hybrid imaging into RT treatment planning, compatible dedicated RT devices are required for accurate patient positioning. In this study, prototype RT positioning devices intended for PET/MR hybrid imaging are introduced and tested toward PET/MR compatibility and image quality. Methods: A prototype flat RT table overlay and two radiofrequency (RF) coil holders that each fix one flexible body matrix RF coil for RT head/neck imaging have been evaluated within this study. MR image quality with the RT head setup was compared to the actual PET/MR setup with a dedicated head RF coil. PET photon attenuation and CT-based attenuation correction (AC) of the hardware components has been quantitatively evaluated by phantom scans. Clinical application of the new RT setup in PET/MR imaging was evaluated in anin vivo study. Results: The RT table overlay and RF coil holders are fully PET/MR compatible. MR phantom and volunteer imaging with the RT head setup revealed high image quality, comparable to images acquired with the dedicated PET/MR head RF coil, albeit with 25% reduced SNR. Repositioning accuracy of the RF coil holders was below 1 mm. PET photon attenuation of the RT table overlay was calculated to be 3.8% and 13.8% for the RF coil holders. With CT-based AC of the devices, the underestimation error was reduced to 0.6% and 0.8%, respectively. Comparable results were found within the patient study. Conclusions: The newly designed RT devices for hybrid PET/MR imaging are PET and MR compatible. The mechanically rigid design and the reproducible positioning allow for straightforward CT-based AC. The systematic evaluation within this study provides the

Machine Learning for Medical Imaging.

Science.gov (United States)

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

Automated medical image segmentation techniques

Directory of Open Access Journals (Sweden)

Sharma Neeraj

2010-01-01

Full Text Available Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

Medical image information system 2001. Development of the medical image information system to risk management- Medical exposure management

International Nuclear Information System (INIS)

Kuranishi, Makoto; Kumagai, Michitomo; Shintani, Mitsuo

2000-01-01

This paper discusses the methods and systems for optimizing the following supplements 10 and 17 for national health and medical care. The supplements 10 and 17 of DICOM (digital imaging and communications in medicine) system, which is now under progress for the purpose to keep compatibility within medical image information system as an international standard, are important for making the cooperation between HIS (hospital information system)/RIS (radiation information system) and modality (imaging instruments). Supplement 10 concerns the system to send the information of patients and their orders through HIS/RIS to modality and 17, the information of modality performed procedure step (MPPS) to HIS/RIS. The latter defines to document patients' exposure, a part of which has not been recognized in Japan. Thus the medical information system can be useful for risk-management of medical exposure in future. (K.H.)

Medical image information system 2001. Development of the medical image information system to risk management- Medical exposure management

Energy Technology Data Exchange (ETDEWEB)

Kuranishi, Makoto; Kumagai, Michitomo; Shintani, Mitsuo [Toyama Medical and Pharmaceutical Univ. (Japan). Hospital

2000-12-01

This paper discusses the methods and systems for optimizing the following supplements 10 and 17 for national health and medical care. The supplements 10 and 17 of DICOM (digital imaging and communications in medicine) system, which is now under progress for the purpose to keep compatibility within medical image information system as an international standard, are important for making the cooperation between HIS (hospital information system)/RIS (radiation information system) and modality (imaging instruments). Supplement 10 concerns the system to send the information of patients and their orders through HIS/RIS to modality and 17, the information of modality performed procedure step (MPPS) to HIS/RIS. The latter defines to document patients' exposure, a part of which has not been recognized in Japan. Thus the medical information system can be useful for risk-management of medical exposure in future. (K.H.)

Clinical applications of SPECT/CT: New hybrid nuclear medicine imaging system

International Nuclear Information System (INIS)

2008-08-01

Interest in multimodality imaging shows no sign of subsiding. New tracers are spreading out the spectrum of clinical applications and innovative technological solutions are preparing the way for yet more modality marriages: hybrid imaging. Single photon emission computed tomography (SPECT) has enabled the evaluation of disease processes based on functional and metabolic information of organs and cells. Integration of X ray computed tomography (CT) into SPECT has recently emerged as a brilliant diagnostic tool in medical imaging, where anatomical details may delineate functional and metabolic information. SPECT/CT has proven to be valuable in oncology. For example, in the case of a patient with metastatic thyroid cancer, neither SPECT nor CT alone could identify the site of malignancy. SPECT/CT, a hybrid image, precisely identified where the surgeon should operate. However SPECT/CT is not just advantageous in oncology. It may also be used as a one-stop-shop for various diseases. Clinical applications with SPECT/CT have started and expanded in developed countries. It has been reported that moving from SPECT alone to SPECT/CT could change diagnoses in 30% of cases. Large numbers of people could therefore benefit from this shift all over the world. This report presents an overview of clinical applications of SPECT/CT and a relevant source of information for nuclear medicine physicians, radiologists and clinical practitioners. This information may also be useful for decision making when allocating resources dedicated to the health care system, a critical issue that is especially important for the development of nuclear medicine in developing countries. In this regard, the IAEA may be heavily involved in the promotion of programmes aimed at the IAEA's coordinated research projects and Technical Cooperation projects

Medical imaging systems

Science.gov (United States)

Frangioni, John V

2013-06-25

A medical imaging system provides simultaneous rendering of visible light and diagnostic or functional images. The system may be portable, and may include adapters for connecting various light sources and cameras in open surgical environments or laparascopic or endoscopic environments. A user interface provides control over the functionality of the integrated imaging system. In one embodiment, the system provides a tool for surgical pathology.

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.

Hybrid statistics-simulations based method for atom-counting from ADF STEM images

Energy Technology Data Exchange (ETDEWEB)

De wael, Annelies, E-mail: annelies.dewael@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); De Backer, Annick [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Jones, Lewys; Nellist, Peter D. [Department of Materials, University of Oxford, Parks Road, OX1 3PH Oxford (United Kingdom); Van Aert, Sandra, E-mail: sandra.vanaert@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium)

2017-06-15

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. - Highlights: • A hybrid method for atom-counting from ADF STEM images is introduced. • Image simulations are incorporated into a statistical framework in a reliable manner. • Limits of the existing methods for atom-counting are far exceeded. • Reliable counting results from an experimental low dose image are obtained. • Progress towards reliable quantitative analysis of beam-sensitive materials is made.

Medical Imaging with Neural Networks

International Nuclear Information System (INIS)

Pattichis, C.; Cnstantinides, A.

1994-01-01

The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors)

Medical imaging and augmented reality. Proceedings

International Nuclear Information System (INIS)

Dohi, Takeyoshi; Sakuma, Ichiro; Liao, Hongen

2008-01-01

This book constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008. The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation. (orig.)

Medical imaging and augmented reality. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Dohi, Takeyoshi [Tokyo Univ. (Japan). Dept. of Mechano-Informatics; Sakuma, Ichiro [Tokyo Univ. (Japan). Dept. of Precision Engineering; Liao, Hongen (eds.) [Tokyo Univ. (Japan). Dept. of Bioengineering

2008-07-01

This book constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008. The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation. (orig.)

A hybrid flower pollination algorithm based modified randomized location for multi-threshold medical image segmentation.

Science.gov (United States)

Wang, Rui; Zhou, Yongquan; Zhao, Chengyan; Wu, Haizhou

2015-01-01

Multi-threshold image segmentation is a powerful image processing technique that is used for the preprocessing of pattern recognition and computer vision. However, traditional multilevel thresholding methods are computationally expensive because they involve exhaustively searching the optimal thresholds to optimize the objective functions. To overcome this drawback, this paper proposes a flower pollination algorithm with a randomized location modification. The proposed algorithm is used to find optimal threshold values for maximizing Otsu's objective functions with regard to eight medical grayscale images. When benchmarked against other state-of-the-art evolutionary algorithms, the new algorithm proves itself to be robust and effective through numerical experimental results including Otsu's objective values and standard deviations.

[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.

Generative Interpretation of Medical Images

DEFF Research Database (Denmark)

Stegmann, Mikkel Bille

2004-01-01

This thesis describes, proposes and evaluates methods for automated analysis and quantification of medical images. A common theme is the usage of generative methods, which draw inference from unknown images by synthesising new images having shape, pose and appearance similar to the analysed images......, handling of non-Gaussian variation by means of cluster analysis, correction of respiratory noise in cardiac MRI, and the extensions to multi-slice two-dimensional time-series and bi-temporal three-dimensional models. The medical applications include automated estimation of: left ventricular ejection...

Medical Imaging with Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Pattichis, C [Department of Computer Science, University of Cyprus, Kallipoleos 75, P.O.Box 537, Nicosia (Cyprus); Cnstantinides, A [Department of Electrical Engineering, Imperial College of Science, Technology and Medicine, London SW7 2BT (United Kingdom)

1994-12-31

The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors). 61 refs, 4 tabs.

Image analysis and modeling in medical image computing. Recent developments and advances.

Science.gov (United States)

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

Quantitative information in medical imaging

International Nuclear Information System (INIS)

Deconinck, F.

1985-01-01

When developing new imaging or image processing techniques, one constantly has in mind that the new technique should provide a better, or more optimal answer to medical tasks than existing techniques do 'Better' or 'more optimal' imply some kind of standard by which one can measure imaging or image processing performance. The choice of a particular imaging modality to answer a diagnostic task, such as the detection of coronary artery stenosis is also based on an implicit optimalisation of performance criteria. Performance is measured by the ability to provide information about an object (patient) to the person (referring doctor) who ordered a particular task. In medical imaging the task is generally to find quantitative information on bodily function (biochemistry, physiology) and structure (histology, anatomy). In medical imaging, a wide range of techniques is available. Each technique has it's own characteristics. The techniques discussed in this paper are: nuclear magnetic resonance, X-ray fluorescence, scintigraphy, positron emission tomography, applied potential tomography, computerized tomography, and compton tomography. This paper provides a framework for the comparison of imaging performance, based on the way the quantitative information flow is altered by the characteristics of the modality

Evidence based medical imaging (EBMI)

International Nuclear Information System (INIS)

Smith, Tony

2008-01-01

Background: The evidence based paradigm was first described about a decade ago. Previous authors have described a framework for the application of evidence based medicine which can be readily adapted to medical imaging practice. Purpose: This paper promotes the application of the evidence based framework in both the justification of the choice of examination type and the optimisation of the imaging technique used. Methods: The framework includes five integrated steps: framing a concise clinical question; searching for evidence to answer that question; critically appraising the evidence; applying the evidence in clinical practice; and, evaluating the use of revised practices. Results: This paper illustrates the use of the evidence based framework in medical imaging (that is, evidence based medical imaging) using the examples of two clinically relevant case studies. In doing so, a range of information technology and other resources available to medical imaging practitioners are identified with the intention of encouraging the application of the evidence based paradigm in radiography and radiology. Conclusion: There is a perceived need for radiographers and radiologists to make greater use of valid research evidence from the literature to inform their clinical practice and thus provide better quality services

Medical imaging technology

CERN Document Server

Haidekker, Mark A

2013-01-01

Biomedical imaging is a relatively young discipline that started with Conrad Wilhelm Roentgen’s discovery of the x-ray in 1885. X-ray imaging was rapidly adopted in hospitals around the world. However, it was the advent of computerized data and image processing that made revolutionary new imaging modalities possible. Today, cross-sections and three-dimensional reconstructions of the organs inside the human body is possible with unprecedented speed, detail and quality. This book provides an introduction into the principles of image formation of key medical imaging modalities: X-ray projection imaging, x-ray computed tomography, magnetic resonance imaging, ultrasound imaging, and radionuclide imaging. Recent developments in optical imaging are also covered. For each imaging modality, the introduction into the physical principles and sources of contrast is provided, followed by the methods of image formation, engineering aspects of the imaging devices, and a discussion of strengths and limitations of the modal...

Visual perception and medical imaging

International Nuclear Information System (INIS)

Jaffe, C.C.

1985-01-01

Medical imaging represents a particularly distinct discipline for image processing since it uniquely depends on the ''expert observer'' and yet models of the human visual system are totally inadequate at the complex level to allow satisfactory prediction of observer response to a given image modification. An illustration of the difficulties in assessing observer performance is shown by a series of optical illustrations which demonstrate that net cognitive behavior is not readily predictable. Although many of these phenomena are often considered as exceptional visual events, the setting of complex images makes it difficult to entirely exclude at least partial operation of these impairments during performance of the diagnostic medical imaging task

Medical hyperspectral imaging: a review

Science.gov (United States)

Lu, Guolan; Fei, Baowei

2014-01-01

Abstract. Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:24441941

An overview of medical image data base

International Nuclear Information System (INIS)

Nishihara, Eitaro

1992-01-01

Recently, the systematization using computers in medical institutions has advanced, and the introduction of hospital information system has been almost completed in the large hospitals with more than 500 beds. But the objects of the management of the hospital information system are text information, and do not include the management of images of enormous quantity. By the progress of image diagnostic equipment, the digitization of medical images has advanced, but the management of images in hospitals does not utilize the merits of digital images. For the purpose of solving these problems, the picture archiving and communication system (PACS) was proposed about ten years ago, which makes medical images into a data base, and enables the on-line access to images from various places in hospitals. The studies have been continued to realize it. The features of medical image data, the present status of utilizing medical image data, the outline of the PACS, the image data base for the PACS, the problems in the realization of the data base and the technical trend, and the state of actual construction of the PACS are reported. (K.I.)

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.

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

Application of stereo-imaging technology to medical field.

Science.gov (United States)

Nam, Kyoung Won; Park, Jeongyun; Kim, In Young; Kim, Kwang Gi

2012-09-01

There has been continuous development in the area of stereoscopic medical imaging devices, and many stereoscopic imaging devices have been realized and applied in the medical field. In this article, we review past and current trends pertaining to the application stereo-imaging technologies in the medical field. We describe the basic principles of stereo vision and visual issues related to it, including visual discomfort, binocular disparities, vergence-accommodation mismatch, and visual fatigue. We also present a brief history of medical applications of stereo-imaging techniques, examples of recently developed stereoscopic medical devices, and patent application trends as they pertain to stereo-imaging medical devices. Three-dimensional (3D) stereo-imaging technology can provide more realistic depth perception to the viewer than conventional two-dimensional imaging technology. Therefore, it allows for a more accurate understanding and analysis of the morphology of an object. Based on these advantages, the significance of stereoscopic imaging in the medical field increases in accordance with the increase in the number of laparoscopic surgeries, and stereo-imaging technology plays a key role in the diagnoses of the detailed morphologies of small biological specimens. The application of 3D stereo-imaging technology to the medical field will help improve surgical accuracy, reduce operation times, and enhance patient safety. Therefore, it is important to develop more enhanced stereoscopic medical devices.

Developments in medical imaging techniques

International Nuclear Information System (INIS)

Kramer, Cornelis

1979-01-01

A review of the developments in medical imaging in the past 25 years shows a strong increase in the number of physical methods which have become available for obtaining images of diagnostic value. It is shown that despite this proliferation of methods the equipment used for obtaining the images can be based on a common structure. Also the resulting images can be characterized by a few relevant parameters which indicate their information content. On the basis of this common architecture a study is made of the potential capabilities of the large number of medical imaging techniques available now and in the future. Also the requirements and possibilities for handling the images obtained and for controlling the diagnostic systems are investigated [fr

21 CFR 892.2040 - Medical image hardcopy device.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical image hardcopy device. 892.2040 Section... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2040 Medical image hardcopy device. (a) Identification. A medical image hardcopy device is a device that produces a visible printed record of a medical...

Stereoscopic medical imaging collaboration system

Science.gov (United States)

Okuyama, Fumio; Hirano, Takenori; Nakabayasi, Yuusuke; Minoura, Hirohito; Tsuruoka, Shinji

2007-02-01

The computerization of the clinical record and the realization of the multimedia have brought improvement of the medical service in medical facilities. It is very important for the patients to obtain comprehensible informed consent. Therefore, the doctor should plainly explain the purpose and the content of the diagnoses and treatments for the patient. We propose and design a Telemedicine Imaging Collaboration System which presents a three dimensional medical image as X-ray CT, MRI with stereoscopic image by using virtual common information space and operating the image from a remote location. This system is composed of two personal computers, two 15 inches stereoscopic parallax barrier type LCD display (LL-151D, Sharp), one 1Gbps router and 1000base LAN cables. The software is composed of a DICOM format data transfer program, an operation program of the images, the communication program between two personal computers and a real time rendering program. Two identical images of 512×768 pixcels are displayed on two stereoscopic LCD display, and both images show an expansion, reduction by mouse operation. This system can offer a comprehensible three-dimensional image of the diseased part. Therefore, the doctor and the patient can easily understand it, depending on their needs.

Classification in Medical Imaging

DEFF Research Database (Denmark)

Chen, Chen

Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... on characterizing human faces and emphysema disease in lung CT images....

Reducing noise component on medical images

Science.gov (United States)

Semenishchev, Evgeny; Voronin, Viacheslav; Dub, Vladimir; Balabaeva, Oksana

2018-04-01

Medical visualization and analysis of medical data is an actual direction. Medical images are used in microbiology, genetics, roentgenology, oncology, surgery, ophthalmology, etc. Initial data processing is a major step towards obtaining a good diagnostic result. The paper considers the approach allows an image filtering with preservation of objects borders. The algorithm proposed in this paper is based on sequential data processing. At the first stage, local areas are determined, for this purpose the method of threshold processing, as well as the classical ICI algorithm, is applied. The second stage uses a method based on based on two criteria, namely, L2 norm and the first order square difference. To preserve the boundaries of objects, we will process the transition boundary and local neighborhood the filtering algorithm with a fixed-coefficient. For example, reconstructed images of CT, x-ray, and microbiological studies are shown. The test images show the effectiveness of the proposed algorithm. This shows the applicability of analysis many medical imaging applications.

Medical Imaging and Infertility.

Science.gov (United States)

Peterson, Rebecca

2016-11-01

Infertility affects many couples, and medical imaging plays a vital role in its diagnosis and treatment. Radiologic technologists benefit from having a broad understanding of infertility risk factors and causes. This article describes the typical structure and function of the male and female reproductive systems, as well as congenital and acquired conditions that could lead to a couple's inability to conceive. Medical imaging procedures performed for infertility diagnosis are discussed, as well as common interventional options available to patients. © 2016 American Society of Radiologic Technologists.

Digital Signal Processing for Medical Imaging Using Matlab

CERN Document Server

Gopi, E S

2013-01-01

This book describes medical imaging systems, such as X-ray, Computed tomography, MRI, etc. from the point of view of digital signal processing. Readers will see techniques applied to medical imaging such as Radon transformation, image reconstruction, image rendering, image enhancement and restoration, and more. This book also outlines the physics behind medical imaging required to understand the techniques being described. The presentation is designed to be accessible to beginners who are doing research in DSP for medical imaging. Matlab programs and illustrations are used wherever possible to reinforce the concepts being discussed.  ·         Acts as a “starter kit” for beginners doing research in DSP for medical imaging; ·         Uses Matlab programs and illustrations throughout to make content accessible, particularly with techniques such as Radon transformation and image rendering; ·         Includes discussion of the basic principles behind the various medical imaging tec...

Medical physics 2013. Abstracts; Medizinische Physik 2013. Abstractband

Energy Technology Data Exchange (ETDEWEB)

Treuer, Harald (ed.) [Koeln Univ. (Germany). Klinik fuer Stereotaxie und Funktionelle Neurochirurgie

2013-07-01

The proceedings of the medical physics conference 2013 include abstract of lectures and poster sessions concerning the following issues: Tele-therapy - application systems, nuclear medicine and molecular imaging, neuromodulation, hearing and technical support, basic dosimetry, NMR imaging -CEST (chemical exchange saturation transfer), medical robotics, magnetic particle imaging, audiology, radiation protection, phase contrast - innovative concepts, particle therapy, brachytherapy, computerized tomography, quantity assurance, hybrid imaging techniques, diffusion and lung NMR imaging, image processing - visualization, cardiac and abdominal NMR imaging.

Effectiveness of a Hybrid Classroom in the Delivery of Medical Terminology Course Content

Science.gov (United States)

Martin, Jeffrey S.; Kreiger, Joan E.; Apicerno, Amy L

2015-01-01

Hybrid courses are emerging as a viable option for content delivery across college campuses. In an attempt to maximize learning outcomes while leveraging resources, one institution used several sections of a Medical Terminology course as a pilot. Traditional and hybrid course delivery were compared utilizing a quantitative research method to…

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.

A survey of medical diagnostic imaging technologies

Energy Technology Data Exchange (ETDEWEB)

Heese, V.; Gmuer, N.; Thomlinson, W.

1991-10-01

The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today`s more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities.

A survey of medical diagnostic imaging technologies

International Nuclear Information System (INIS)

Heese, V.; Gmuer, N.; Thomlinson, W.

1991-10-01

The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today's more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities

Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

Science.gov (United States)

De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

2017-06-01

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

Overview of deep learning in medical imaging.

Science.gov (United States)

Suzuki, Kenji

2017-09-01

The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a

A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows.

Science.gov (United States)

Blattner, Timothy; Keyrouz, Walid; Bhattacharyya, Shuvra S; Halem, Milton; Brady, Mary

2017-12-01

Designing applications for scalability is key to improving their performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with data dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) improves programmer productivity when implementing hybrid workflows for multi-core and multi-GPU systems. The Hybrid Task Graph Scheduler (HTGS) is an abstract execution model, framework, and API that increases programmer productivity when implementing hybrid workflows for such systems. HTGS manages dependencies between tasks, represents CPU and GPU memories independently, overlaps computations with disk I/O and memory transfers, keeps multiple GPUs occupied, and uses all available compute resources. Through these abstractions, data motion and memory are explicit; this makes data locality decisions more accessible. To demonstrate the HTGS application program interface (API), we present implementations of two example algorithms: (1) a matrix multiplication that shows how easily task graphs can be used; and (2) a hybrid implementation of microscopy image stitching that reduces code size by ≈ 43% compared to a manually coded hybrid workflow implementation and showcases the minimal overhead of task graphs in HTGS. Both of the HTGS-based implementations show good performance. In image stitching the HTGS implementation achieves similar performance to the hybrid workflow implementation. Matrix multiplication with HTGS achieves 1.3× and 1.8× speedup over the multi-threaded OpenBLAS library for 16k × 16k and 32k × 32k size matrices, respectively.

Radioisotopes and medical imaging in Sri Lanka

International Nuclear Information System (INIS)

Jayasinghe, J.M.A.C.

1993-01-01

The article deals with the use of X-rays and magnetic resonance imaging in medical diagnosis in its introduction. Then it elaborates on the facilities in the field of medical imaging for diagnosis, in Sri Lanka. The use of Technetium-99m in diagnostic medicine as well as the future of medical imaging in Sri Lanka is also dealt with

A hybrid peptide PTS that facilitates transmembrane delivery and its application for the rapid in vivo imaging via near-infrared fluorescence imaging

Directory of Open Access Journals (Sweden)

Xuejiao eYan

2016-03-01

Full Text Available Background and purpose: Intravital imaging provides invaluable readouts for clinical diagnoses and therapies and shows great potential in the design of individualized drug dosage regimes. Ts is a mammalian free cell membrane-penetrating peptide. This study aimed to introduce a novel approach to the design of a cancer-selective peptide on the basis of a membrane-penetrating peptide and to explore its potential as a carrier of medical substances. Experimental approach: Ts was linked with a αvβ3-binding peptide P1c to create a hybrid referred to as PTS. The hybrid was labeled with an FITC or Cy5.5 as an imaging indicator to evaluate its in vitro and in vivo bioactivity. Key results: Hemolysis tests proved that in comparison with Ts, PTS caused similar or even less leakage of human erythrocytes at concentrations of up to 1 mmol/L. Flow cytometry assay and confocal microscopy demonstrated the following. 1 P1c alone could target and mostly halt at the cancer cell membrane. 2 Ts alone could not bind to the membrane sufficiently. 3 P1c greatly enhanced the binding affinity of PTS with MDA-MB-231 breast cancer cells that upregulated αvβ3. 4 Ts conferred PTS with the ability to traverse a cell membrane and thus facilitate the transmembrane delivery of imaging probes. In vivo near-infrared fluorescence (NIRF imaging demonstrated that the imaging probes were rapidly concentrated in a MDA-MB-231 tumor tissue within 1 h after intravenous injection. Conclusions and implications: PTS exhibited the capability of targeting specific tumors and greatly facilitating the transmembrane delivery of imaging probes.

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

A survey of medical diagnostic imaging technologies

Energy Technology Data Exchange (ETDEWEB)

Heese, V.; Gmuer, N.; Thomlinson, W.

1991-10-01

The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today's more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities.

Medical image segmentation using improved FCM

Institute of Scientific and Technical Information of China (English)

ZHANG XiaoFeng; ZHANG CaiMing; TANG WenJing; WEI ZhenWen

2012-01-01

Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more complex. Fuzzy Cmeans,as an effective tool to deal with PVE,however,is faced with great challenges in efficiency.Aiming at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two phases.The first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM algorithm.Compared with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying results.Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing.

Medical imaging, PACS, and imaging informatics: retrospective.

Science.gov (United States)

Huang, H K

2014-01-01

Historical reviews of PACS (picture archiving and communication system) and imaging informatics development from different points of view have been published in the past (Huang in Euro J Radiol 78:163-176, 2011; Lemke in Euro J Radiol 78:177-183, 2011; Inamura and Jong in Euro J Radiol 78:184-189, 2011). This retrospective attempts to look at the topic from a different angle by identifying certain basic medical imaging inventions in the 1960s and 1970s which had conceptually defined basic components of PACS guiding its course of development in the 1980s and 1990s, as well as subsequent imaging informatics research in the 2000s. In medical imaging, the emphasis was on the innovations at Georgetown University in Washington, DC, in the 1960s and 1970s. During the 1980s and 1990s, research and training support from US government agencies and public and private medical imaging manufacturers became available for training of young talents in biomedical physics and for developing the key components required for PACS development. In the 2000s, computer hardware and software as well as communication networks advanced by leaps and bounds, opening the door for medical imaging informatics to flourish. Because many key components required for the PACS operation were developed by the UCLA PACS Team and its collaborative partners in the 1980s, this presentation is centered on that aspect. During this period, substantial collaborative research efforts by many individual teams in the US and in Japan were highlighted. Credits are due particularly to the Pattern Recognition Laboratory at Georgetown University, and the computed radiography (CR) development at the Fuji Electric Corp. in collaboration with Stanford University in the 1970s; the Image Processing Laboratory at UCLA in the 1980s-1990s; as well as the early PACS development at the Hokkaido University, Sapporo, Japan, in the late 1970s, and film scanner and digital radiography developed by Konishiroku Photo Ind. Co. Ltd

The present and future of medical imaging physics

International Nuclear Information System (INIS)

Bao Shanglian; Zhang Huailing; Huang Feizeng

2004-01-01

The physics of medical imaging is one of the main branches of medical physics, which trains medical physicists for the R and D of medical imaging equipment, clinical application of this equipment as well as R and D in medical physics. The development of medical imaging physics is one of the biggest programs aimed at making China a world manufacturer both in hardware and software. However, there is no formal medical physics in China as yet. The scale of education and training, and the level of manufacture of medical imaging equipment are very low compared with developed countries. It is therefore imperative for China to accelerate the rate of development to satisfy her requirements. Amongst other priorities, building up the education and training system in medical physics and setting up a staff of medical physicists in hospitals is the most urgent thing

Viewpoints on Medical Image Processing: From Science to Application

Science.gov (United States)

Deserno (né Lehmann), Thomas M.; Handels, Heinz; Maier-Hein (né Fritzsche), Klaus H.; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-01-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment. PMID:24078804

Viewpoints on Medical Image Processing: From Science to Application.

Science.gov (United States)

Deserno Né Lehmann, Thomas M; Handels, Heinz; Maier-Hein Né Fritzsche, Klaus H; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-05-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.

Medical image diagnosis of liver cancer using artificial intelligence

International Nuclear Information System (INIS)

Kondo, Tadashi; Ueno, Junji; Takao, Shoichiro

2010-01-01

A revised Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of liver cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS). It is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis. (author)

Diagnostic imaging in undergraduate medical education: an expanding role

International Nuclear Information System (INIS)

Miles, K.A.

2005-01-01

Radiologists have been involved in anatomy instruction for medical students for decades. However, recent technical advances in radiology, such as multiplanar imaging, 'virtual endoscopy', functional and molecular imaging, and spectroscopy, offer new ways in which to use imaging for teaching basic sciences to medical students. The broad dissemination of picture archiving and communications systems is making such images readily available to medical schools, providing new opportunities for the incorporation of diagnostic imaging into the undergraduate medical curriculum. Current reforms in the medical curriculum and the establishment of new medical schools in the UK further underline the prospects for an expanding role for imaging in medical education. This article reviews the methods by which diagnostic imaging can be used to support the learning of anatomy and other basic sciences

Applications of VLSI circuits to medical imaging

International Nuclear Information System (INIS)

O'Donnell, M.

1988-01-01

In this paper the application of advanced VLSI circuits to medical imaging is explored. The relationship of both general purpose signal processing chips and custom devices to medical imaging is discussed using examples of fabricated chips. In addition, advanced CAD tools for silicon compilation are presented. Devices built with these tools represent a possible alternative to custom devices and general purpose signal processors for the next generation of medical imaging systems

Army medical imaging system: ARMIS

International Nuclear Information System (INIS)

Siedband, M.P.; Kramp, D.C.

1987-01-01

Recent advances of stimulable phosphor screens, data cards using optical storage means, and new personal computers with image processing capability have made possible the design of economical filmless medical imaging systems. The addition of communication links means that remote interpretation of images is also possible. The Army Medical Imaging System uses stimulable phosphor screens, digital readout, a small computer, an optical digital data card device, and a DIN/PACS link. Up to 200 images can be stored in the computer hard disk for rapid recall and reading by the radiologist. The computer permits image processing, annotation, insertion of text, and control of the system. Each device contains an image storage RAM and communicates with the computer via the small computer systems interface. Data compression is used to reduce the required storage capacity and transmission times of the 1-mB images. The credit card-size optical data cards replace film and can store 12 or more images. The data cards can be read on an independent viewer. The research is supported by the U.S. Army Biomedical Research and Development Laboratory

Remote-sensing image encryption in hybrid domains

Science.gov (United States)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

A special designed library for medical imaging applications

International Nuclear Information System (INIS)

Lymberopoulos, D.; Kotsopoulos, S.; Zoupas, V.; Yoldassis, N.; Spyropoulos, C.

1994-01-01

The present paper deals with a sophisticated and flexible library of medical purpose image processing routines. It contains modules for simple as well as advanced gray or colour image processing. This library offers powerful features for medical image processing and analysis applications, thus providing the physician with a means of analyzing and estimating medical images in order to accomplish their diagnostic procedures

Topics in medical image processing and computational vision

CERN Document Server

Jorge, Renato

2013-01-01

  The sixteen chapters included in this book were written by invited experts of international recognition and address important issues in Medical Image Processing and Computational Vision, including: Object Recognition, Object Detection, Object Tracking, Pose Estimation, Facial Expression Recognition, Image Retrieval, Data Mining, Automatic Video Understanding and Management, Edges Detection, Image Segmentation, Modelling and Simulation, Medical thermography, Database Systems, Synthetic Aperture Radar and Satellite Imagery.   Different applications are addressed and described throughout the book, comprising: Object Recognition and Tracking, Facial Expression Recognition, Image Database, Plant Disease Classification, Video Understanding and Management, Image Processing, Image Segmentation, Bio-structure Modelling and Simulation, Medical Imaging, Image Classification, Medical Diagnosis, Urban Areas Classification, Land Map Generation.   The book brings together the current state-of-the-art in the various mul...

Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

Science.gov (United States)

Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

2018-04-01

Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

Medical image informatics infrastructure design and applications.

Science.gov (United States)

Huang, H K; Wong, S T; Pietka, E

1997-01-01

Picture archiving and communication systems (PACS) is a system integration of multimodality images and health information systems designed for improving the operation of a radiology department. As it evolves, PACS becomes a hospital image document management system with a voluminous image and related data file repository. A medical image informatics infrastructure can be designed to take advantage of existing data, providing PACS with add-on value for health care service, research, and education. A medical image informatics infrastructure (MIII) consists of the following components: medical images and associated data (including PACS database), image processing, data/knowledge base management, visualization, graphic user interface, communication networking, and application oriented software. This paper describes these components and their logical connection, and illustrates some applications based on the concept of the MIII.

Hybrid-organic photodetectors for radiography. Final report; Hybrid organische Photodetektoren fuer die Radiographie. Abschlussbericht

Energy Technology Data Exchange (ETDEWEB)

Schmidt, Oliver [Siemens Healthcare GmbH, Erlangen (Germany); Bonrad, Klaus [Merck KGaA, Darmstadt (Germany); Adam, Jens; Kraus, Tobias [INM - Leibniz-Institut fuer Neue Materialien gGmbH, Saarbruecken (Germany); Gimmler, Christoph [CAN GmbH, Hamburg (Germany)

2016-02-15

HOP-X aimed to combine the advantages of nanotechnology and organic electronics for application in medical X-ray imaging in order to enable more cost-effective imaging at lower dose. Solution-processing of organic semiconductors enables easy hybridization with X-ray absorbers and processing on large areas. In this project, nano-sized scintillators and quantum dots have been synthesized and characterized as X-ray absorbers. Organic semiconductor materials have been identified which allow charge carrier extraction from layers with a thickness of up to 200 μm. Hybrid-organic photodiodes have been processed and the ideal mixture of organic semiconductor and inorganic X-ray absorber was determined. This mixture provide a high X-ray absorption and an efficient charge carrier extraction at the same time. Photodiodes have been integrated on TFT-matrix backplanes in order to demonstrate the concept in X-ray imagers.

A special designed library for medical imaging applications

Energy Technology Data Exchange (ETDEWEB)

Lymberopoulos, D; Kotsopoulos, S; Zoupas, V; Yoldassis, N [Departmeent of Electrical Engineering, University of Patras, Patras 26 110 Greece (Greece); Spyropoulos, C [School of Medicine, Regional University Hospital, University of Patras, Patras 26 110 Greece (Greece)

1994-12-31

The present paper deals with a sophisticated and flexible library of medical purpose image processing routines. It contains modules for simple as well as advanced gray or colour image processing. This library offers powerful features for medical image processing and analysis applications, thus providing the physician with a means of analyzing and estimating medical images in order to accomplish their diagnostic procedures. 6 refs, 1 figs.

Generation of hybrid sinograms for the recovery of kV-CT images with metal artifacts for helical tomotherapy

International Nuclear Information System (INIS)

Jeon, Hosang; Park, Dahl; Kim, Wontaek; Ki, Yongkan; Kim, Yong Ho; Lee, Ju Hye; Kim, Dongwon; Youn, Hanbean; Nam, Jiho; Lee, Jayoung; Kim, Ho Kyung

2015-01-01

Purpose: The overall goal of this study is to restore kilovoltage computed tomography (kV-CT) images which are disfigured by patients’ metal prostheses. By generating a hybrid sinogram that is a combination of kV and megavoltage (MV) projection data, the authors suggest a novel metal artifact-reduction (MAR) method that retains the image quality to match that of kV-CT and simultaneously restores the information of metal prostheses lost due to photon starvation. Methods: CT projection data contain information about attenuation coefficients and the total length of the attenuation. By normalizing raw kV projections with their own total lengths of attenuation, mean attenuation projections were obtained. In the same manner, mean density projections of MV-CT were obtained by the normalization of MV projections resulting from the forward projection of density-calibrated MV-CT images with the geometric parameters of the kV-CT device. To generate the hybrid sinogram, metal-affected signals of the kV sinogram were identified and replaced by the corresponding signals of the MV sinogram following a density calibration step with kV data. Filtered backprojection was implemented to reconstruct the hybrid CT image. To validate the authors’ approach, they simulated four different scenarios for three heads and one pelvis using metallic rod inserts within a cylindrical phantom. Five inserts describing human body elements were also included in the phantom. The authors compared the image qualities among the kV, MV, and hybrid CT images by measuring the contrast-to-noise ratio (CNR), the signal-to-noise ratio (SNR), the densities of all inserts, and the spatial resolution. In addition, the MAR performance was compared among three existing MAR methods and the authors’ hybrid method. Finally, for clinical trials, the authors produced hybrid images of three patients having dental metal prostheses to compare their MAR performances with those of the kV, MV, and three existing MAR

Desktop publishing and medical imaging: paper as hardcopy medium for digital images.

Science.gov (United States)

Denslow, S

1994-08-01

Desktop-publishing software and hardware has progressed to the point that many widely used word-processing programs are capable of printing high-quality digital images with many shades of gray from black to white. Accordingly, it should be relatively easy to print digital medical images on paper for reports, instructional materials, and in research notes. Components were assembled that were necessary for extracting image data from medical imaging devices and converting the data to a form usable by word-processing software. A system incorporating these components was implemented in a medical setting and has been operating for 18 months. The use of this system by medical staff has been monitored.

The Orthanc Ecosystem for Medical Imaging.

Science.gov (United States)

Jodogne, Sébastien

2018-05-03

This paper reviews the components of Orthanc, a free and open-source, highly versatile ecosystem for medical imaging. At the core of the Orthanc ecosystem, the Orthanc server is a lightweight vendor neutral archive that provides PACS managers with a powerful environment to automate and optimize the imaging flows that are very specific to each hospital. The Orthanc server can be extended with plugins that provide solutions for teleradiology, digital pathology, or enterprise-ready databases. It is shown how software developers and research engineers can easily develop external software or Web portals dealing with medical images, with minimal knowledge of the DICOM standard, thanks to the advanced programming interface of the Orthanc server. The paper concludes by introducing the Stone of Orthanc, an innovative toolkit for the cross-platform rendering of medical images.

Deep Learning in Medical Image Analysis.

Science.gov (United States)

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

STEM image simulation with hybrid CPU/GPU programming

International Nuclear Information System (INIS)

Yao, Y.; Ge, B.H.; Shen, X.; Wang, Y.G.; Yu, R.C.

2016-01-01

STEM image simulation is achieved via hybrid CPU/GPU programming under parallel algorithm architecture to speed up calculation on a personal computer (PC). To utilize the calculation power of a PC fully, the simulation is performed using the GPU core and multi-CPU cores at the same time to significantly improve efficiency. GaSb and an artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. - Highlights: • STEM image simulation is achieved by hybrid CPU/GPU programming under parallel algorithm architecture to speed up the calculation in the personal computer (PC). • In order to fully utilize the calculation power of the PC, the simulation is performed by GPU core and multi-CPU cores at the same time so efficiency is improved significantly. • GaSb and artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. The results reveal some unintuitive phenomena about the contrast variation with the atom numbers.

STEM image simulation with hybrid CPU/GPU programming

Energy Technology Data Exchange (ETDEWEB)

Yao, Y., E-mail: yaoyuan@iphy.ac.cn; Ge, B.H.; Shen, X.; Wang, Y.G.; Yu, R.C.

2016-07-15

STEM image simulation is achieved via hybrid CPU/GPU programming under parallel algorithm architecture to speed up calculation on a personal computer (PC). To utilize the calculation power of a PC fully, the simulation is performed using the GPU core and multi-CPU cores at the same time to significantly improve efficiency. GaSb and an artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. - Highlights: • STEM image simulation is achieved by hybrid CPU/GPU programming under parallel algorithm architecture to speed up the calculation in the personal computer (PC). • In order to fully utilize the calculation power of the PC, the simulation is performed by GPU core and multi-CPU cores at the same time so efficiency is improved significantly. • GaSb and artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. The results reveal some unintuitive phenomena about the contrast variation with the atom numbers.

A hierarchical SVG image abstraction layer for medical imaging

Science.gov (United States)

Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer

2010-03-01

As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

Science.gov (United States)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

A high performance parallel approach to medical imaging

International Nuclear Information System (INIS)

Frieder, G.; Frieder, O.; Stytz, M.R.

1988-01-01

Research into medical imaging using general purpose parallel processing architectures is described and a review of the performance of previous medical imaging machines is provided. Results demonstrating that general purpose parallel architectures can achieve performance comparable to other, specialized, medical imaging machine architectures is presented. A new back-to-front hidden-surface removal algorithm is described. Results demonstrating the computational savings obtained by using the modified back-to-front hidden-surface removal algorithm are presented. Performance figures for forming a full-scale medical image on a mesh interconnected multiprocessor are presented

Hybrid Photoacoustic/Ultrasound Tomograph for Real-Time Finger Imaging.

Science.gov (United States)

Oeri, Milan; Bost, Wolfgang; Sénégond, Nicolas; Tretbar, Steffen; Fournelle, Marc

2017-10-01

We report a target-enclosing, hybrid tomograph with a total of 768 elements based on capacitive micromachined ultrasound transducer technology and providing fast, high-resolution 2-D/3-D photoacoustic and ultrasound tomography tailored to finger imaging. A freely programmable ultrasound beamforming platform sampling data at 80 MHz was developed to realize plane wave transmission under multiple angles. A multiplexing unit enables the connection and control of a large number of elements. Fast image reconstruction is provided by GPU processing. The tomograph is composed of four independent and fully automated movable arc-shaped transducers, allowing imaging of all three finger joints. The system benefits from photoacoustics, yielding high optical contrast and enabling visualization of finger vascularization, and ultrasound provides morphologic information on joints and surrounding tissue. A diode-pumped, Q-switched Nd:YAG laser and an optical parametric oscillator are used to broaden the spectrum of emitted wavelengths to provide multispectral imaging. Custom-made optical fiber bundles enable illumination of the region of interest in the plane of acoustic detection. Precision in positioning of the probe in motion is ensured by use of a motor-driven guide slide. The current position of the probe is encoded by the stage and used to relate ultrasound and photoacoustic signals to the corresponding region of interest of the suspicious finger joint. The system is characterized in phantoms and a healthy human finger in vivo. The results obtained promise to provide new opportunities in finger diagnostics and establish photoacoustic/ultrasound-tomography in medical routine. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

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...

TSV last for hybrid pixel detectors: Application to particle physics and imaging experiments

CERN Document Server

Henry, D; Berthelot, A; Cuchet, R; Chantre, C; Campbell, M

Hybrid pixel detectors are now widely used in particle physics experiments and at synchrotron light sources. They have also stimulated growing interest in other fields and, in particular, in medical imaging. Through the continuous pursuit of miniaturization in CMOS it has been possible to increase the functionality per pixel while maintaining or even shrinking pixel dimensions. The main constraint on the more extensive use of the technology in all fields is the cost of module building and the difficulty of covering large areas seamlessly [1]. On another hand, in the field of electronic component integration, a new approach has been developed in the last years, called 3D Integration. This concept, based on using the vertical axis for component integration, allows improving the global performance of complex systems. Thanks to this technology, the cost and the form factor of components could be decreased and the performance of the global system could be enhanced. In the field of radiation imaging detectors the a...

Clinical perspectives of hybrid proton-fluorine magnetic resonance imaging and spectroscopy.

Science.gov (United States)

Wolters, Martijn; Mohades, Seyede G; Hackeng, Tilman M; Post, Mark J; Kooi, Marianne E; Backes, Walter H

2013-05-01

The number of applications of fluorine 19 (19F) magnetic resonance (MR) imaging and spectroscopy in biomedical and clinical research is steadily growing. The 100% natural abundance of fluorine and its relatively high sensitivity for MR (83% to that of protons) make it an interesting nucleus for a wide range of MR applications. Fluorinated contrast media have a number of advantages over the conventionally used gadolinium-based or iron-based contrast agents. The absence of an endogenous fluorine background intensity in the human body facilitates reliable quantification of fluorinated contrast medium or drugs. Anatomy can be visualized separately with proton MR imaging, creating the application of hybrid hydrogen 1 (1H)/19F MR imaging. The availability of 2 channels (ie, the 1H and 19F channels) enables dual-targeted molecular imaging. Recently, novel developments have emerged on fluorine-based contrast media in preclinical studies and imaging techniques. The developments in fluorine MR seem promising for clinical applications, with contributions in therapy monitoring, assessment of lung function, angiography, and molecular imaging. This review outlines the translation from recent advances in preclinical MR imaging and spectroscopy to future perspectives of clinical hybrid 1H/19/F MR imaging applications.

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

Science.gov (United States)

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Imaging techniques for medical diagnosis

International Nuclear Information System (INIS)

Gudden, F.

1982-01-01

In the last few decades, science, engineering and medicine have combinded to improve the quality of our lives to a level previously unimagined. Within the framework of medical engineering - the field of activity of the Medical Engineering Group of Siemens AG - diagnostic image-generating systems have played an important role in effecting these changes and improvements. The importance of these systems to the success of the Group is clearly evident. Diagnostic imaging systems account for 65% of the sales achieved by this Group. In this article an overview is presented of the major innovations and the aims of developments in the field of imaging systems. (orig.)

A Fast Enhanced Secure Image Chaotic Cryptosystem Based on Hybrid Chaotic Magic Transform

Directory of Open Access Journals (Sweden)

Srinivas Koppu

2017-01-01

Full Text Available An enhanced secure image chaotic cryptosystem has been proposed based on hybrid CMT-Lanczos algorithm. We have achieved fast encryption and decryption along with privacy of images. The pseudorandom generator has been used along with Lanczos algorithm to generate root characteristics and eigenvectors. Using hybrid CMT image, pixels are shuffled to accomplish excellent randomness. Compared with existing methods, the proposed method had more robustness to various attacks: brute-force attack, known cipher plaintext, chosen-plaintext, security key space, key sensitivity, correlation analysis and information entropy, and differential attacks. Simulation results show that the proposed methods give better result in protecting images with low-time complexity.

Hybridization State Detection of DNA-Functionalized Gold Nanoparticles Using Hyperspectral Imaging

Directory of Open Access Journals (Sweden)

Richard C. Murdock

2017-01-01

Full Text Available Hyperspectral imaging has the unique ability of capturing spectral data for multiple wavelengths at each pixel in an image. This gives the ability to distinguish, with certainty, different nanomaterials and/or distinguish nanomaterials from biological materials. In this study, 4 nm and 13 nm gold nanoparticles (Au NPs were synthesized, functionalized with complimentary oligonucleotides, and hybridized to form large networks of NPs. Scattering spectra were collected from each sample (unfunctionalized, functionalized, and hybridized and evaluated. The spectra showed unique peaks for each size of Au NP sample and also exhibited narrowing and intensifying of the spectra as the NPs were functionalized and then subsequently hybridized. These spectra are different from normal aggregation effects where the LSPR and reflected spectrum broaden and are red-shifted. Rather, this appears to be dependent on the ability to control the interparticle distance through oligonucleotide length, which is also investigated through the incorporation of a poly-A spacer. Also, hybridized Au NPs were exposed to cells with no adverse effects and retained their unique spectral signatures. With the ability to distinguish between hybridization states at nearly individual NP levels, this could provide a new method of tracking the intracellular actions of nanomaterials as well as extracellular biosensing applications.

Design and realization of a fast low noise electronics for a hybrid pixel X-ray detector dedicated to small animal imaging

International Nuclear Information System (INIS)

Chantepie, B.

2008-12-01

Since the invention of computerized tomography (CT), charge integration detector were widely employed for X-ray biomedical imaging applications. Nevertheless, other options exist. A new technology of direct detection using semiconductors has been developed for high energy physics instrumentation. This new technology, called hybrid pixel detector, works in photon counting mode and allows for selecting the minimum energy of the counted photons. The ImXgam research team at CPPM develops the PIXSCAN demonstrator, a CT-scanner using the hybrid pixel detector XPAD. The aim of this project is to evaluate the improvement in image quality and in dose delivered during X-ray examinations of a small animal. After a first prototype of a hybrid pixel detector XPAD1 proving the feasibility of the project, a complete imager XPAD2 was designed and integrated in the PIXSCAN demonstrator. Since then, with the evolution of microelectronic industry, important improvements are conceivable. To reducing the size of pixels and to improving the energy resolution of detectors, a third design XPAD3 was conceived and will be soon integrated in a second generation of PIXSCAN demonstrator. In this project, my thesis work consisted in taking part to the design of the detector readout electronics, to the characterization of the chips and of the hybrid pixel detectors, and also to the definition of a auto-zeroing architecture for pixels. The first and second chapters present X-ray medical imaging and particle detection with semi-conductors and its modelling. The third chapter deals with the specifications of electronic circuits for imaging applications first for analog pixels then for digital pixels and describes the general architecture of the integrated circuits. The validation tests are presented in the fourth chapter while the last chapter gives an account of expected changes in pixel electronics

The semiotics of medical image Segmentation.

Science.gov (United States)

Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M

2018-02-01

As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.

Trends in medical image processing

International Nuclear Information System (INIS)

Robilotta, C.C.

1987-01-01

The function of medical image processing is analysed, mentioning the developments, the physical agents, and the main categories, as conection of distortion in image formation, detectability increase, parameters quantification, etc. (C.G.C.) [pt

Medical imaging systems

Science.gov (United States)

Frangioni, John V [Wayland, MA

2012-07-24

A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remains in a subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may also employ dyes or other fluorescent substances associated with antibodies, antibody fragments, or ligands that accumulate within a region of diagnostic significance. In one embodiment, the system provides an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide that is used to capture images. In another embodiment, the system is configured for use in open surgical procedures by providing an operating area that is closed to ambient light. More broadly, the systems described herein may be used in imaging applications where a visible light image may be usefully supplemented by an image formed from fluorescent emissions from a fluorescent substance that marks areas of functional interest.

Nonreference Medical Image Edge Map Measure

Directory of Open Access Journals (Sweden)

Karen Panetta

2014-01-01

Full Text Available Edge detection is a key step in medical image processing. It is widely used to extract features, perform segmentation, and further assist in diagnosis. A poor quality edge map can result in false alarms and misses in cancer detection algorithms. Therefore, it is necessary to have a reliable edge measure to assist in selecting the optimal edge map. Existing reference based edge measures require a ground truth edge map to evaluate the similarity between the generated edge map and the ground truth. However, the ground truth images are not available for medical images. Therefore, a nonreference edge measure is ideal for medical image processing applications. In this paper, a nonreference reconstruction based edge map evaluation (NREM is proposed. The theoretical basis is that a good edge map keeps the structure and details of the original image thus would yield a good reconstructed image. The NREM is based on comparing the similarity between the reconstructed image with the original image using this concept. The edge measure is used for selecting the optimal edge detection algorithm and optimal parameters for the algorithm. Experimental results show that the quantitative evaluations given by the edge measure have good correlations with human visual analysis.

REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICA

Directory of Open Access Journals (Sweden)

О. E. Prokopchenko

2015-09-01

Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article & based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematica may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

Molecular photoacoustic imaging

Directory of Open Access Journals (Sweden)

Frogh Jafarian Dehkordi

2015-04-01

Full Text Available Background: Hybrid imaging modalities which simultaneously benefit from capabilities of combined modalities provides an opportunity to modify quality of the images which can be obtained by each of the combined imaging systems. One of the imaging modalities, emerged in medical research area as a hybrid of ultrasound imaging and optical imaging, is photoacoustic imaging which apply ultrasound wave generated by tissue, after receiving laser pulse, to produce medical images. Materials and Methods: In this review, using keywords such as photoacoustic, optoacoustic, laser-ultrasound, thermoacoustic at databases such as PubMed and ISI, studies performed in the field of photoacoustic and related findings were evaluated. Results: Photoacoustic imaging, acquiring images with high contrast and desired resolution, provides an opportunity to perform physiologic and anatomic studies. Because this technique does not use ionizing radiation, it is not restricted by the limitation of the ionizing-based imaging systems therefore it can be used noninvasively to make images from cell, vessels, whole body imaging of the animal and distinguish tumor from normal tissue. Conclusion: Photoacoustic imaging is a new method in preclinical researches which can be used in various physiologic and anatomic studies. This method, because of application of non-ionizing radiation, may resolve limitation of radiation based method in diagnostic assessments.

Medical imaging and the Internet

International Nuclear Information System (INIS)

Jones, D.N.; Carr, P.

1995-01-01

A brief introduction to the INTERNET and its benefits for those involved in nuclear medical imaging is given. In Australia, depending on the type of institution/department involved, connection to the INTERNET may be obtained via the Australian Academic and Research Network or through a commercial provider. The recent proliferation of WWW servers has also resulted in multiple medical imaging databases and teaching resources becoming available to the user. Some Newsgroups and WWW addresses related to radiology are provided. 3 refs

A digital library for medical imaging activities

Science.gov (United States)

dos Santos, Marcelo; Furuie, Sérgio S.

2007-03-01

This work presents the development of an electronic infrastructure to make available a free, online, multipurpose and multimodality medical image database. The proposed infrastructure implements a distributed architecture for medical image database, authoring tools, and a repository for multimedia documents. Also it includes a peer-reviewed model that assures quality of dataset. This public repository provides a single point of access for medical images and related information to facilitate retrieval tasks. The proposed approach has been used as an electronic teaching system in Radiology as well.

Feature Detector and Descriptor for Medical Images

Science.gov (United States)

Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

2009-02-01

The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

First observation of Cherenkov ring images using hybrid photon detectors

International Nuclear Information System (INIS)

Albrecht, E.; Wilkinson, G.; Bibby, J.H.; Giles, R.; Harnew, N.; Smale, N.; Brook, N.H.; Halley, A.W.; O'Shea, V.; French, M.; Gibson, V.; Wotton, S.A.; Schomaker, R.

1998-01-01

A ring-imaging Cherenkov detector, equipped with hybrid photon detectors, has been operated in a charged-particle beam. Focussed ring images from various particle types were detected using silica aerogel, air and C 4 F 10 gas radiators. The detector, a prototype for the CERN LHC-B experiment, is described and first observations are reported. (orig.)

First observation of Cherenkov ring images using hybrid photon detectors

Energy Technology Data Exchange (ETDEWEB)

Albrecht, E.; Wilkinson, G. [European Organization for Nuclear Research, Geneva (Switzerland). Div. Particle Physics Experiments; Barber, G.; Duane, A.; John, M.; Miller, D.G.; Websdale, D. [Imperial College of Science Technology and Medicine, Blackett Laboratory, Prince Consort Road, London SW7 2AZ (United Kingdom); Bibby, J.H.; Giles, R.; Harnew, N.; Smale, N. [University of Oxford, Department of Nuclear Physics, Keble Road, Oxford OX1 3RH (United Kingdom); Brook, N.H.; Halley, A.W.; O`Shea, V. [University of Glasgow, Department of Physics, Glasgow G12 8QQ (United Kingdom); French, M. [Rutherford Appleton Laboratory, Chilton, Didcot, Oxon OX11 0QX (United Kingdom); Gibson, V.; Wotton, S.A. [University of Cambridge, Cavendish Laboratory, Madingley Road, Cambridge CB3 0HE (United Kingdom); Schomaker, R. [Delft Electronic Products BV, 9300 AB Roden (Netherlands)

1998-07-11

A ring-imaging Cherenkov detector, equipped with hybrid photon detectors, has been operated in a charged-particle beam. Focussed ring images from various particle types were detected using silica aerogel, air and C{sub 4}F{sub 10} gas radiators. The detector, a prototype for the CERN LHC-B experiment, is described and first observations are reported. (orig.)

A framework for integration of heterogeneous medical imaging networks.

Science.gov (United States)

Viana-Ferreira, Carlos; Ribeiro, Luís S; Costa, Carlos

2014-01-01

Medical imaging is increasing its importance in matters of medical diagnosis and in treatment support. Much is due to computers that have revolutionized medical imaging not only in acquisition process but also in the way it is visualized, stored, exchanged and managed. Picture Archiving and Communication Systems (PACS) is an example of how medical imaging takes advantage of computers. To solve problems of interoperability of PACS and medical imaging equipment, the Digital Imaging and Communications in Medicine (DICOM) standard was defined and widely implemented in current solutions. More recently, the need to exchange medical data between distinct institutions resulted in Integrating the Healthcare Enterprise (IHE) initiative that contains a content profile especially conceived for medical imaging exchange: Cross Enterprise Document Sharing for imaging (XDS-i). Moreover, due to application requirements, many solutions developed private networks to support their services. For instance, some applications support enhanced query and retrieve over DICOM objects metadata. This paper proposes anintegration framework to medical imaging networks that provides protocols interoperability and data federation services. It is an extensible plugin system that supports standard approaches (DICOM and XDS-I), but is also capable of supporting private protocols. The framework is being used in the Dicoogle Open Source PACS.

Collaborative Affordances of Hybrid Patient Record Technologies in Medical Work

DEFF Research Database (Denmark)

Houben, Steven; Frost, Mads; Bardram, Jakob E

2015-01-01

explored the integration of paper and digital technology, there are still a wide range of open issues in the design of technologies that integrate digital and paper-based medical records. This paper studies the use of one such novel technology, called the Hybrid Patient Record (HyPR), that is designed......The medical record is a central artifact used to organize, communicate and coordinate information related to patient care. Despite recent deployments of electronic health records (EHR), paper medical records are still widely used because of the affordances of paper. Although a number of approaches...... to digitally augment a paper medical record. We report on two studies: a field study in which we describe the benefits and challenges of using a combination of electronic and paper-based medical records in a large university hospital and a deployment study in which we analyze how 8 clinicians used the Hy...

REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICS

Directory of Open Access Journals (Sweden)

O. Ye. Prokopchenko

2015-10-01

Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article and based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematics may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve  the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

Hybrid Imaging Labels: Providing the Link Between Mass Spectrometry-Based Molecular Pathology and Theranostics

Science.gov (United States)

Buckle, Tessa; van der Wal, Steffen; van Malderen, Stijn J.M.; Müller, Larissa; Kuil, Joeri; van Unen, Vincent; Peters, Ruud J.B.; van Bemmel, Margaretha E.M.; McDonnell, Liam A.; Velders, Aldrik H.; Koning, Frits; Vanhaeke, Frank; van Leeuwen, Fijs W. B.

2017-01-01

Background: Development of theranostic concepts that include inductively coupled plasma mass spectrometry (ICP-MS) and laser ablation ICP-MS (LA-ICP-MS) imaging can be hindered by the lack of a direct comparison to more standardly used methods for in vitro and in vivo evaluation; e.g. fluorescence or nuclear medicine. In this study a bimodal (or rather, hybrid) tracer that contains both a fluorescent dye and a chelate was used to evaluate the existence of a direct link between mass spectrometry (MS) and in vitro and in vivo molecular imaging findings using fluorescence and radioisotopes. At the same time, the hybrid label was used to determine whether the use of a single isotope label would allow for MS-based diagnostics. Methods: A hybrid label that contained both a DTPA chelate (that was coordinated with either 165Ho or 111In) and a Cy5 fluorescent dye was coupled to the chemokine receptor 4 (CXCR4) targeting peptide Ac-TZ14011 (hybrid-Cy5-Ac-TZ4011). This receptor targeting tracer was used to 1) validate the efficacy of (165Ho-based) mass-cytometry in determining the receptor affinity via comparison with fluorescence-based flow cytometry (Cy5), 2) evaluate the microscopic binding pattern of the tracer in tumor cells using both fluorescence confocal imaging (Cy5) and LA-ICP-MS-imaging (165Ho), 3) compare in vivo biodistribution patterns obtained with ICP-MS (165Ho) and radiodetection (111In) after intravenous administration of hybrid-Cy5-Ac-TZ4011 in tumor-bearing mice. Finally, LA-ICP-MS-imaging (165Ho) was linked to fluorescence-based analysis of excised tissue samples (Cy5). Results: Analysis with both mass-cytometry and flow cytometry revealed a similar receptor affinity, respectively 352 ± 141 nM and 245 ± 65 nM (p = 0.08), but with a much lower detection sensitivity for the first modality. In vitro LA-ICP-MS imaging (165Ho) enabled clear discrimination between CXCR4 positive and negative cells, but fluorescence microscopy was required to determine the

A hierarchical approach of hybrid image classification for land use and land cover mapping

Directory of Open Access Journals (Sweden)

Rahdari Vahid

2018-01-01

Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

Developments in medical image processing and computational vision

CERN Document Server

Jorge, Renato

2015-01-01

This book presents novel and advanced topics in Medical Image Processing and Computational Vision in order to solidify knowledge in the related fields and define their key stakeholders. It contains extended versions of selected papers presented in VipIMAGE 2013 – IV International ECCOMAS Thematic Conference on Computational Vision and Medical Image, which took place in Funchal, Madeira, Portugal, 14-16 October 2013.  The twenty-two chapters were written by invited experts of international recognition and address important issues in medical image processing and computational vision, including: 3D vision, 3D visualization, colour quantisation, continuum mechanics, data fusion, data mining, face recognition, GPU parallelisation, image acquisition and reconstruction, image and video analysis, image clustering, image registration, image restoring, image segmentation, machine learning, modelling and simulation, object detection, object recognition, object tracking, optical flow, pattern recognition, pose estimat...

Improved Image Encryption for Real-Time Application over Wireless Communication Networks using Hybrid Cryptography Technique

Directory of Open Access Journals (Sweden)

Kazeem B. Adedeji

2016-12-01

Full Text Available Advances in communication networks have enabled organization to send confidential data such as digital images over wireless networks. However, the broadcast nature of wireless communication channel has made it vulnerable to attack from eavesdroppers. We have developed a hybrid cryptography technique, and we present its application to digital images as a means of improving the security of digital image for transmission over wireless communication networks. The hybrid technique uses a combination of a symmetric (Data Encryption Standard and asymmetric (Rivest Shamir Adleman cryptographic algorithms to secure data to be transmitted between different nodes of a wireless network. Three different image samples of type jpeg, png and jpg were tested using this technique. The results obtained showed that the hybrid system encrypt the images with minimal simulation time, and high throughput. More importantly, there is no relation or information between the original images and their encrypted form, according to Shannon’s definition of perfect security, thereby making the system much more secure.

Applied medical image processing a basic course

CERN Document Server

Birkfellner, Wolfgang

2014-01-01

A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data and illustrations on an accompanying CD-ROM or companion website. Organized as a complete textbook, it provides an overview of the physics of medical image processing and discusses image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction.

Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

Directory of Open Access Journals (Sweden)

R. V. V. Krishna

2016-10-01

Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

Image files of planarians analyzed by in situ hybridication and immunohistochemical staining - Plabrain DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Plabrain DB Image files of planarians analyzed by in situ hybridication and immunohistochemical... staining Data detail Data name Image files of planarians analyzed by in situ hybridication and immunohistochemical...sion patterns by whole-mount in situ hybridication and also protein distribution by immunohistochemical...Images are displayed in A list of image files of planarians analyzed by in situ hybridication and immunohistochemical...le search URL - Data acquisition method Whole-mount in situ hybridication, immunohistochemical staining Data

Future of X-ray phase imaging in medical imaging technology

International Nuclear Information System (INIS)

Momose, Atsushi

2007-01-01

Weakly absorbing materials, such as biological, soft tissues, can be imaged by generating contrast due to the phase shift of X-rays. In the past decade, several methods for X-ray phase imaging were proposed and demonstrated. The performance of X-ray phase imaging is attractive in the field of medical imaging technology, and its development for practical use is expected. Many methods, however, have been developed under the assumption of the use of synchrotron radiation, which is an obstacle to practical use. The method based on Talbot (-Lau) interferometry enables us to use a compact X-ray source, and its development is expected as a breakthrough for medical applications. (author)

Physics and engineering of medical imaging

International Nuclear Information System (INIS)

Guzzardi, R.

1987-01-01

The ever-developing technology of medical imaging has a continuous and significant impact on the practice of medicine as well as on clinical research activity. The information and level of accuracy obtained by an imaging methodology is a complex result of a multidisciplinary effort of physics, engineering, electronics, chemistry and medicine. In this book, the state of the art is described for NMR, ultrasound, X-ray CT, nuclear medicine, positron tomography and other imaging modalities. For every imaging modality, the most important clinical applications are described together with the delineation of problems and future needs. Furthermore, specific sections of the book are devoted to general aspects of medical imaging, such as reconstruction techniques, 2-D and 3-D display, quality control, archiving, market trends and correlative assessment

An interactive medical image segmentation framework using iterative refinement.

Science.gov (United States)

Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

2017-04-01

Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Content Based Medical Image Retrieval for Histopathological, CT and MRI Images

Directory of Open Access Journals (Sweden)

Swarnambiga AYYACHAMY

2013-09-01

Full Text Available A content based approach is followed for medical images. The purpose of this study is to access the stability of these methods for medical image retrieval. The methods used in color based retrieval for histopathological images are color co-occurrence matrix (CCM and histogram with meta features. For texture based retrieval GLCM (gray level co-occurrence matrix and local binary pattern (LBP were used. For shape based retrieval canny edge detection and otsu‘s method with multivariable threshold were used. Texture and shape based retrieval were implemented using MRI (magnetic resonance images. The most remarkable characteristics of the article are its content based approach for each medical imaging modality. Our efforts were focused on the initial visual search. From our experiment, histogram with meta features in color based retrieval for histopathological images shows a precision of 60 % and recall of 30 %. Whereas GLCM in texture based retrieval for MRI images shows a precision of 70 % and recall of 20 %. Shape based retrieval for MRI images shows a precision of 50% and recall of 25 %. The retrieval results shows that this simple approach is successful.

Wavelets in medical imaging

International Nuclear Information System (INIS)

Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.

2012-01-01

The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

Wavelets in medical imaging

Energy Technology Data Exchange (ETDEWEB)

Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H. [Sharda University, SET, Department of Electronics and Communication, Knowledge Park 3rd, Gr. Noida (India); University of Kocaeli, Department of Mathematics, 41380 Kocaeli (Turkey); Istanbul Aydin University, Department of Computer Engineering, 34295 Istanbul (Turkey); Sharda University, SET, Department of Mathematics, 32-34 Knowledge Park 3rd, Greater Noida (India)

2012-07-17

The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

Moonshot Acceleration Factor: Medical Imaging.

Science.gov (United States)

Sevick-Muraca, Eva M; Frank, Richard A; Giger, Maryellen L; Mulshine, James L

2017-11-01

Medical imaging is essential to screening, early diagnosis, and monitoring responses to cancer treatments and, when used with other diagnostics, provides guidance for clinicians in choosing the most effective patient management plan that maximizes survivorship and quality of life. At a gathering of agency officials, patient advocacy organizations, industry/professional stakeholder groups, and clinical/basic science academicians, recommendations were made on why and how one should build a "cancer knowledge network" that includes imaging. Steps to accelerate the translation and clinical adoption of cancer discoveries to meet the goals of the Cancer Moonshot include harnessing computational power and architectures, developing data sharing policies, and standardizing medical imaging and in vitro diagnostics. Cancer Res; 77(21); 5717-20. ©2017 AACR . ©2017 American Association for Cancer Research.

Resolution enhancement in medical ultrasound imaging.

Science.gov (United States)

Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

2015-01-01

Image resolution enhancement is a problem of considerable interest in all medical imaging modalities. Unlike general purpose imaging or video processing, for a very long time, medical image resolution enhancement has been based on optimization of the imaging devices. Although some recent works purport to deal with image postprocessing, much remains to be done regarding medical image enhancement via postprocessing, especially in ultrasound imaging. We face a resolution improvement issue in the case of medical ultrasound imaging. We propose to investigate this problem using multidimensional autoregressive (AR) models. Noting that the estimation of the envelope of an ultrasound radio frequency (RF) signal is very similar to the estimation of classical Fourier-based power spectrum estimation, we theoretically show that a domain change and a multidimensional AR model can be used to achieve super-resolution in ultrasound imaging provided the order is estimated correctly. Here, this is done by means of a technique that simultaneously estimates the order and the parameters of a multidimensional model using relevant regression matrix factorization. Doing so, the proposed method specifically fits ultrasound imaging and provides an estimated envelope. Moreover, an expression that links the theoretical image resolution to both the image acquisition features (such as the point spread function) and a postprocessing feature (the AR model) order is derived. The overall contribution of this work is threefold. First, it allows for automatic resolution improvement. Through a simple model and without any specific manual algorithmic parameter tuning, as is used in common methods, the proposed technique simply and exclusively uses the ultrasound RF signal as input and provides the improved B-mode as output. Second, it allows for the a priori prediction of the improvement in resolution via the knowledge of the parametric model order before actual processing. Finally, to achieve the

Shape analysis in medical image analysis

CERN Document Server

Tavares, João

2014-01-01

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

Science.gov (United States)

Kim, Hyunjun; Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu; Sim, Sung-Han

2017-09-07

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

Signal Processing in Medical Ultrasound B-mode Imaging

International Nuclear Information System (INIS)

Song, Tai Kyong

2000-01-01

Ultrasonic imaging is the most widely used modality among modern imaging device for medical diagnosis and the system performance has been improved dramatically since early 90's due to the rapid advances in DSP performance and VLSI technology that made it possible to employ more sophisticated algorithms. This paper describes 'main stream' digital signal processing functions along with the associated implementation considerations in modern medical ultrasound imaging systems. Topics covered include signal processing methods for resolution improvement, ultrasound imaging system architectures, roles and necessity of the applications of DSP and VLSI technology in the development of the medical ultrasound imaging systems, and array signal processing techniques for ultrasound focusing

Is there any advantage from the hybrid imaging diagnostic?

International Nuclear Information System (INIS)

Kostadinova, I.

2012-01-01

The hybrid imaging methods- Single Photon Emission Tomography-Computer Tomography / SPECT-CT / and Positron Emission Tomography-Computer Tomography / PET-CT/ allow receiving of combined image of two different techniques. In such a way it is possible to superimpose detailed anatomical image of the multislice spiral computer tomography with specific and sensitive molecular images of the SPECT and PET in a single study, allowing utilization of the full possibilities of the both techniques. They have advantages and disadvantages, which basically stem from the differences in the used radiopharmaceuticals and their physical properties. In PET-CT-positron emitters are applied, most often 18F and 11C, while-in SPECT-CT - single photon emitters, most often 99mTc and 131I. A disadvantage of PET is a high cost, which is produced in cyclotron and its logistics is complicated. The great advantage of PET is its better spatial resolution, compared to SPECT, because of the possibility to for simultaneous detection of pared photons and better registration. These techniques, especially PET-CT are nowadays the most increasing imaging methods in the world in making diagnosis, staging and following the effect of treatment in patients with oncological, neurological, cardiological, orthopedic diseases and infections. Recently, they are applied for the purposes of radiotherapy planning on the basis of the metabolically active tumour. As a final result, compared to the conventional techniques- roentgenography, computer tomography and magnetic resonance imaging, it is possible in many cases to make an early and more precise diagnosis and to safe time for the patient for adequate treatment. As a conclusion it is clear, that the hybrid imaging has future and its application will increase in future

The future of three-dimensional medical imaging

International Nuclear Information System (INIS)

Peter, T.M.

1996-01-01

The past 15 years have witnessed an explosion in medical imaging technology, and none more so than in the tomographic imaging modalities of CT and MRI. Prior to 1975, 3-D imaging was largely performed in the minds of radiologists and surgeons, assisted by the modalities of conventional x-ray tomography and stereoscopic radiography. However today, with the advent of imaging techniques which ower their existence to computer technology, three-dimensional image acquisition is fast becoming the norm and the clinician finally has access to sets of data that represent the entire imaged volume. Stereoscopic image visualization has already begun to reappear as a viable means of visualizing 3 D medical images. The future of 3-D imaging is exciting and will undoubtedly move further in the direction of virtual reality. (author)

Implementation methods of medical image sharing for collaborative health care based on IHE XDS-I profile.

Science.gov (United States)

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Sun, Jianyong; Ling, Tonghui; Wang, Mingqing; Bak, Peter

2015-10-01

IHE XDS-I profile proposes an architecture model for cross-enterprise medical image sharing, but there are only a few clinical implementations reported. Here, we investigate three pilot studies based on the IHE XDS-I profile to see whether we can use this architecture as a foundation for image sharing solutions in a variety of health-care settings. The first pilot study was image sharing for cross-enterprise health care with federated integration, which was implemented in Huadong Hospital and Shanghai Sixth People's Hospital within the Shanghai Shen-Kang Hospital Management Center; the second pilot study was XDS-I-based patient-controlled image sharing solution, which was implemented by the Radiological Society of North America (RSNA) team in the USA; and the third pilot study was collaborative imaging diagnosis with electronic health-care record integration in regional health care, which was implemented in two districts in Shanghai. In order to support these pilot studies, we designed and developed new image access methods, components, and data models such as RAD-69/WADO hybrid image retrieval, RSNA clearinghouse, and extension of metadata definitions in both the submission set and the cross-enterprise document sharing (XDS) registry. We identified several key issues that impact the implementation of XDS-I in practical applications, and conclude that the IHE XDS-I profile is a theoretically good architecture and a useful foundation for medical image sharing solutions across multiple regional health-care providers.

From Roentgen to magnetic resonance imaging: the history of medical imaging.

Science.gov (United States)

Scatliff, James H; Morris, Peter J

2014-01-01

Medical imaging has advanced in remarkable ways since the discovery of x-rays 120 years ago. Today's radiologists can image the human body in intricate detail using computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and various other modalities. Such technology allows for improved screening, diagnosis, and monitoring of disease, but it also comes with risks. Many imaging modalities expose patients to ionizing radiation, which potentially increases their risk of developing cancer in the future, and imaging may also be associated with possible allergic reactions or risks related to the use of intravenous contrast agents. In addition, the financial costs of imaging are taxing our health care system, and incidental findings can trigger anxiety and further testing. This issue of the NCMJ addresses the pros and cons of medical imaging and discusses in detail the following uses of medical imaging: screening for breast cancer with mammography, screening for osteoporosis and monitoring of bone mineral density with dual-energy x-ray absorptiometry, screening for congenital hip dysplasia in infants with ultrasound, and evaluation of various heart conditions with cardiac imaging. Together, these articles show the challenges that must be met as we seek to harness the power of today's imaging technologies, as well as the potential benefits that can be achieved when these hurdles are overcome.

Physics instrumentation for medical imaging

International Nuclear Information System (INIS)

Townsend, D.W.

1993-01-01

The first Nobel Physics Prize, awarded in 1901, went to Wilhelm Röntgen for his discovery of X-rays in 1895. This, and the most recent physics Nobel, to Georges Charpak last year for his detector developments, span several generations of applied science. As well as helping to launch the science of atomic physics, Röntgen's discovery also marked the dawn of a medical science - radiography - using beams of various kinds to image what otherwise cannot be seen. Ever since, physicists and radiologists have worked hand in hand to improve imaging techniques and widen their medical applications

Physics instrumentation for medical imaging

Energy Technology Data Exchange (ETDEWEB)

Townsend, D. W. [Geneva University Hospital, Geneva (Switzerland)

1993-04-15

The first Nobel Physics Prize, awarded in 1901, went to Wilhelm Röntgen for his discovery of X-rays in 1895. This, and the most recent physics Nobel, to Georges Charpak last year for his detector developments, span several generations of applied science. As well as helping to launch the science of atomic physics, Röntgen's discovery also marked the dawn of a medical science - radiography - using beams of various kinds to image what otherwise cannot be seen. Ever since, physicists and radiologists have worked hand in hand to improve imaging techniques and widen their medical applications.

Evaluation of a hybrid paper-electronic medication management system at a residential aged care facility.

Science.gov (United States)

Elliott, Rohan A; Lee, Cik Yin; Hussainy, Safeera Y

2016-06-01

Objectives The aims of the study were to investigate discrepancies between general practitioners' paper medication orders and pharmacy-prepared electronic medication administration charts, back-up paper charts and dose-administration aids, as well as delays between prescribing, charting and administration, at a 90-bed residential aged care facility that used a hybrid paper-electronic medication management system. Methods A cross-sectional audit of medication orders, medication charts and dose-administration aids was performed to identify discrepancies. In addition, a retrospective audit was performed of delays between prescribing and availability of an updated electronic medication administration chart. Medication administration records were reviewed retrospectively to determine whether discrepancies and delays led to medication administration errors. Results Medication records for 88 residents (mean age 86 years) were audited. Residents were prescribed a median of eight regular medicines (interquartile range 5-12). One hundred and twenty-five discrepancies were identified. Forty-seven discrepancies, affecting 21 (24%) residents, led to a medication administration error. The most common discrepancies were medicine omission (44.0%) and extra medicine (19.2%). Delays from when medicines were prescribed to when they appeared on the electronic medication administration chart ranged from 18min to 98h. On nine occasions (for 10% of residents) the delay contributed to missed doses, usually antibiotics. Conclusion Medication discrepancies and delays were common. Improved systems for managing medication orders and charts are needed. What is known about the topic? Hybrid paper-electronic medication management systems, in which prescribers' orders are transcribed into an electronic system by pharmacy technicians and pharmacists to create medication administration charts, are increasingly replacing paper-based medication management systems in Australian residential aged care

Medical Image Registration and Surgery Simulation

DEFF Research Database (Denmark)

Bro-Nielsen, Morten

1996-01-01

This thesis explores the application of physical models in medical image registration and surgery simulation. The continuum models of elasticity and viscous fluids are described in detail, and this knowledge is used as a basis for most of the methods described here. Real-time deformable models......, and the use of selective matrix vector multiplication. Fluid medical image registration A new and faster algorithm for non-rigid registration using viscous fluid models is presented. This algorithm replaces the core part of the original algorithm with multi-resolution convolution using a new filter, which...... growth is also presented. Using medical knowledge about the growth processes of the mandibular bone, a registration algorithm for time sequence images of the mandible is developed. Since this registration algorithm models the actual development of the mandible, it is possible to simulate the development...

Radiology and Enterprise Medical Imaging Extensions (REMIX).

Science.gov (United States)

Erdal, Barbaros S; Prevedello, Luciano M; Qian, Songyue; Demirer, Mutlu; Little, Kevin; Ryu, John; O'Donnell, Thomas; White, Richard D

2018-02-01

Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of "big imaging data," as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.

Radically Reducing Radiation Exposure during Routine Medical Imaging

Science.gov (United States)

Exposure to radiation from medical imaging in the United States has increased dramatically. NCI and several partner organizations sponsored a 2011 summit to promote efforts to reduce radiation exposure from medical imaging.

A Kalman filter technique applied for medical image reconstruction

International Nuclear Information System (INIS)

Goliaei, S.; Ghorshi, S.; Manzuri, M. T.; Mortazavi, M.

2011-01-01

Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Image reconstruction is essential for medical images for some applications such as suppression of noise or de-blurring the image in order to provide images with better quality and contrast. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as the most popular one known as filtered back projection. In this paper we introduce a Kalman filter technique which is operated in time domain for medical image reconstruction. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of reconstructed image becomes better in terms of contract and transparency. It is also seen that as the number of projection increases the error index decreases.

A review of m-health in medical imaging.

Science.gov (United States)

Perera, Chandrashan Mahendra; Chakrabarti, Rahul

2015-02-01

The increasing capabilities of camera-equipped mobile phones have led to a growing body of evidence regarding their use in medical imaging across a broad range of medical specialties. This article reviews the current evidence for the use of mobile health (m-health) in medical imaging. We performed a structured review of the published literature regarding m-health in medical imaging using the Medline, PubMed, and Web of Science databases (January 2002-August 2013). The two authors independently extracted data regarding type of specialty, purpose, and study design of publications. In total, 235 articles were identified. The majority of studies were case reports or noncomparative product validation studies. The greatest volume of publications originated in the fields of radiology (21%), dermatology (15%), laboratory techniques (15%), and plastic surgery (12%). Among these studies, m-health was used as diagnostic aids, for patient monitoring, and to improve communication between health practitioners. With the growing use of mobile phones for medical imaging, considerations need to be given to informed consent, privacy, image storage and transfer, and guidelines for healthcare workers and patients. There are several novel uses of mobile devices for medical imaging that show promise across a variety of areas and subspecialties of healthcare. Currently, studies are mostly exploratory in nature. To validate these devices, studies with higher methodological rigor are required.

Large-scale retrieval for medical image analytics: A comprehensive review.

Science.gov (United States)

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Medical emergencies in the imaging department of a university hospital: event and imaging characteristics.

Science.gov (United States)

van Tonder, F C; Sutherland, T; Smith, R J; Chock, J M E; Santamaria, J D

2013-01-01

We aimed to describe the characteristics of medical emergencies that occurred in the medical imaging department (MID) of a university hospital in Melbourne, Australia. A database of 'Respond Medical Emergency Team (MET)' and 'Respond Blue' calls was retrospectively examined for the period June 2003 to November 2010 in relation to events that occurred in the MID. The hospital medical imaging database was also examined in relation to these events and, where necessary, patients' notes were reviewed. Ethics approval was granted by the hospital ethics review board. There were 124 medical emergency calls in the MID during the study period, 28% Respond Blue and 72% Respond MET. Of these 124 calls, 26% occurred outside of usual work hours and 12% involved cardiac arrest. The most common reasons for the emergency calls were seizures (14%) and altered conscious state (13%). Contrast anaphylaxis precipitated the emergency in 4% of cases. In 83% of cases the emergency calls were for patients attending the MID for diagnostic imaging, the remainder being for a procedure. Of the scheduled imaging techniques, 45% were for computed tomography. The scheduled imaging was abandoned due to the emergency in 12% of cases. When performed, imaging informed patient management in 34% of cases in diagnostic imaging and in all cases in the context of image-guided procedures. Medical emergency calls in the MID often occurred outside usual work hours and were attributed to a range of medical problems. The emergencies occurred in relation to all imaging techniques and imaging informed patient management in many cases. Crown Copyright © 2012. Published by Elsevier Ireland Ltd. All rights reserved.

Tissues segmentation based on multi spectral medical images

Science.gov (United States)

Li, Ya; Wang, Ying

2017-11-01

Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

Invitation to medical image processing

International Nuclear Information System (INIS)

Kitasaka, Takayuki; Suenaga, Yasuhito; Mori, Kensaku

2010-01-01

This medical essay explains the present state of CT image processing technology about its recognition, acquisition and visualization for computer-assisted diagnosis (CAD) and surgery (CAS), and future view. Medical image processing has a series of history of its original start from the discovery of X-ray to its application to diagnostic radiography, its combination with the computer for CT, multi-detector raw CT, leading to 3D/4D images for CAD and CAS. CAD is performed based on the recognition of normal anatomical structure of human body, detection of possible abnormal lesion and visualization of its numerical figure into image. Actual instances of CAD images are presented here for chest (lung cancer), abdomen (colorectal cancer) and future body atlas (models of organs and diseases for imaging), a recent national project: computer anatomy. CAS involves the surgical planning technology based on 3D images, navigation of the actual procedure and of endoscopy. As guidance to beginning technological image processing, described are the national and international community like related academic societies, regularly conducting congresses, textbooks and workshops, and topics in the field like computed anatomy of an individual patient for CAD and CAS, its data security and standardization. In future, protective medicine is in authors' view based on the imaging technology, e.g., daily life CAD of individuals ultimately, as exemplified in the present body thermometer and home sphygmometer, to monitor one's routine physical conditions. (T.T.)

Hybrid simulation using mixed reality for interventional ultrasound imaging training.

Science.gov (United States)

Freschi, C; Parrini, S; Dinelli, N; Ferrari, M; Ferrari, V

2015-07-01

Ultrasound (US) imaging offers advantages over other imaging modalities and has become the most widespread modality for many diagnostic and interventional procedures. However, traditional 2D US requires a long training period, especially to learn how to manipulate the probe. A hybrid interactive system based on mixed reality was designed, implemented and tested for hand-eye coordination training in diagnostic and interventional US. A hybrid simulator was developed integrating a physical US phantom and a software application with a 3D virtual scene. In this scene, a 3D model of the probe with its relative scan plane is coherently displayed with a 3D representation of the phantom internal structures. An evaluation study of the diagnostic module was performed by recruiting thirty-six novices and four experts. The performances of the hybrid (HG) versus physical (PG) simulator were compared. After the training session, each novice was required to visualize a particular target structure. The four experts completed a 5-point Likert scale questionnaire. Seventy-eight percentage of the HG novices successfully visualized the target structure, whereas only 45% of the PG reached this goal. The mean scores from the questionnaires were 5.00 for usefulness, 4.25 for ease of use, 4.75 for 3D perception, and 3.25 for phantom realism. The hybrid US training simulator provides ease of use and is effective as a hand-eye coordination teaching tool. Mixed reality can improve US probe manipulation training.

Patients radiation protection in medical imaging. Conference proceedings

International Nuclear Information System (INIS)

2011-12-01

This document brings together the available presentations given at the conference organised by the French society of radiation protection about patients radiation protection in medical imaging. Twelve presentations (slides) are compiled in this document and deal with: 1 - Medical exposure of the French population: methodology and results (Bernard Aubert, IRSN); 2 - What indicators for the medical exposure? (Cecile Etard, IRSN); 3 - Guidebook of correct usage of medical imaging examination (Philippe Grenier, Pitie-Salpetriere hospital); 4 - Radiation protection optimization in pediatric imaging (Hubert Ducou-Le-Pointe, Aurelien Bouette (Armand-Trousseau children hospital); 5 - Children's exposure to image scanners: epidemiological survey (Marie-Odile Bernier, IRSN); 6 - Management of patient's irradiation: from image quality to good practice (Thierry Solaire, General Electric); 7 - Dose optimization in radiology (Cecile Salvat (Lariboisiere hospital); 8 - Cancer detection in the breast cancer planned screening program - 2004-2009 era (Agnes Rogel, InVS); 9 - Mammographic exposures - radiobiological effects - radio-induced DNA damages (Catherine Colin, Lyon Sud hospital); 10 - Breast cancer screening program - importance of non-irradiating techniques (Anne Tardivon, Institut Curie); 11 - Radiation protection justification for the medical imaging of patients over the age of 50 (Michel Bourguignon, ASN); 12 - Search for a molecular imprint for the discrimination between radio-induced and sporadic tumors (Sylvie Chevillard, CEA)

Segmentation of medical images using explicit anatomical knowledge

Science.gov (United States)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

Mesh Processing in Medical Image Analysis

DEFF Research Database (Denmark)

The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....

Practical guide to quality assurance in medical imaging

International Nuclear Information System (INIS)

Moores, M.; Watkinson, S.; Pearcy, J.; Henshaw, E.T.

1987-01-01

This volume forms an important part of the response to a growing need to ensure the same and cost-effective use of ionizing radiations for the benefit of both staff and patients. The authors provide guidance to implementing and running quality assurance programs in medical imaging departments. The treatment provides an overview of all the tests which need to be carried out in medical imaging, and the text contains step-by-step guidance as to how to perform and interpret the results of medical imaging

Introduction to Medical Image Analysis

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

Evaluation Of Medical Fluoroscopy Imaging

International Nuclear Information System (INIS)

Hartana, Budi; Santoso

2000-01-01

It has been done to evaluate image system of medical fluoroscopic machine by Leeds Test Object (LTO). Two x-ray potentials of 70 kV and 40-60 kV were used to evaluate image by LTO on monitor and oscilloscope. Performance of imaging system decreased for some parameters of video signal, linearity of television scan, contras threshold of 4.5%, distortion integral of 65.1%, and focus uniformity decrease to edge image. Comparison of field diameter of television image to intensifier field vertically and horizontally were respectively 221:230 and 205:230, symmetrically vignetting, spatial resolution limit is 1.26 lp/mm

Improved Interactive Medical-Imaging System

Science.gov (United States)

Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

2003-01-01

An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

Artificial intelligence and medical imaging. Expert systems and image analysis

International Nuclear Information System (INIS)

Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

1987-01-01

This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

Ontology modularization to improve semantic medical image annotation.

Science.gov (United States)

Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

2011-02-01

Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results. Copyright © 2010 Elsevier Inc. All rights reserved.

Development of 3-D Medical Image VIsualization System

African Journals Online (AJOL)

User

uses standard 2-D medical imaging inputs and generates medical images of human body parts ... light wave from points on the 3-D object(s) in ... tools, and communication bandwidth cannot .... locations along the track that correspond with.

Leadership and power in medical imaging

Energy Technology Data Exchange (ETDEWEB)

Yielder, Jill [School of Health and Community Studies, Unitec New Zealand, Private Bag 92 025, Mt Albert, Auckland (New Zealand)]. E-mail: jyielder@unitec.ac.nz

2006-11-15

This article examines the concept of professional leadership in medical imaging. It explores the context of power issues in which such leadership is located, the differences between leadership and management, the qualities needed for effective leadership and how an individual's psychology may affect it. The article concludes that in the current climate of change and development, the medical imaging profession needs strong and appropriate leadership to profile the profession effectively and to lead it through to a more autonomous future.

Leadership and power in medical imaging

International Nuclear Information System (INIS)

Yielder, Jill

2006-01-01

This article examines the concept of professional leadership in medical imaging. It explores the context of power issues in which such leadership is located, the differences between leadership and management, the qualities needed for effective leadership and how an individual's psychology may affect it. The article concludes that in the current climate of change and development, the medical imaging profession needs strong and appropriate leadership to profile the profession effectively and to lead it through to a more autonomous future

Silica nanoparticle-based dual imaging colloidal hybrids: cancer cell imaging and biodistribution

Directory of Open Access Journals (Sweden)

Lee H

2015-08-01

Full Text Available Haisung Lee,1 Dongkyung Sung,2 Jinhoon Kim,3 Byung-Tae Kim,3 Tuntun Wang,4 Seong Soo A An,5 Soo-Won Seo,6 Dong Kee Yi4 1Molecular Diagnostics, In Vitro Diagnostics Unit, New Business Division, SK Telecom, 2Department of Life Sciences, Graduate School of Korea University, 3Interdisciplinary Graduate Program of Biomedical Engineering, School of Medicine, Sungkyunkwan University, Samsung Medical Center, 4Department of Chemistry, Myongji University, Seoul, 5Department of Bionanotechnology, Gachon Medical Research Institute, Gachon University, Seongnam, 6Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Republic of Korea Abstract: In this study, fluorescent dye-conjugated magnetic resonance (MR imaging agents were investigated in T mode. Gadolinium-conjugated silica nanoparticles were successfully synthesized for both MR imaging and fluorescence diagnostics. Polyamine and polycarboxyl functional groups were modified chemically on the surface of the silica nanoparticles for efficient conjugation of gadolinium ions. The derived gadolinium-conjugated silica nanoparticles were investigated by zeta potential analysis, transmission electron microscopy, inductively coupled plasma mass spectrometry, and energy dispersive x-ray spectroscopy. MR equipment was used to investigate their use as contrast-enhancing agents in T1 mode under a 9.4 T magnetic field. In addition, we tracked the distribution of the gadolinium-conjugated nanoparticles in both lung cancer cells and organs in mice. Keywords: dual bioimaging, MR imaging, silica colloid, T1 contrast imaging, nanohybrid

A new concept for medical imaging centered on cellular phone technology.

Directory of Open Access Journals (Sweden)

Yair Granot

2008-04-01

Full Text Available According to World Health Organization reports, some three quarters of the world population does not have access to medical imaging. In addition, in developing countries over 50% of medical equipment that is available is not being used because it is too sophisticated or in disrepair or because the health personnel are not trained to use it. The goal of this study is to introduce and demonstrate the feasibility of a new concept in medical imaging that is centered on cellular phone technology and which may provide a solution to medical imaging in underserved areas. The new system replaces the conventional stand-alone medical imaging device with a new medical imaging system made of two independent components connected through cellular phone technology. The independent units are: a a data acquisition device (DAD at a remote patient site that is simple, with limited controls and no image display capability and b an advanced image reconstruction and hardware control multiserver unit at a central site. The cellular phone technology transmits unprocessed raw data from the patient site DAD and receives and displays the processed image from the central site. (This is different from conventional telemedicine where the image reconstruction and control is at the patient site and telecommunication is used to transmit processed images from the patient site. The primary goal of this study is to demonstrate that the cellular phone technology can function in the proposed mode. The feasibility of the concept is demonstrated using a new frequency division multiplexing electrical impedance tomography system, which we have developed for dynamic medical imaging, as the medical imaging modality. The system is used to image through a cellular phone a simulation of breast cancer tumors in a medical imaging diagnostic mode and to image minimally invasive tissue ablation with irreversible electroporation in a medical imaging interventional mode.

Hybrid-organic photodetectors for radiography. Final report

International Nuclear Information System (INIS)

Schmidt, Oliver; Bonrad, Klaus; Adam, Jens; Kraus, Tobias; Gimmler, Christoph

2016-02-01

HOP-X aimed to combine the advantages of nanotechnology and organic electronics for application in medical X-ray imaging in order to enable more cost-effective imaging at lower dose. Solution-processing of organic semiconductors enables easy hybridization with X-ray absorbers and processing on large areas. In this project, nano-sized scintillators and quantum dots have been synthesized and characterized as X-ray absorbers. Organic semiconductor materials have been identified which allow charge carrier extraction from layers with a thickness of up to 200 μm. Hybrid-organic photodiodes have been processed and the ideal mixture of organic semiconductor and inorganic X-ray absorber was determined. This mixture provide a high X-ray absorption and an efficient charge carrier extraction at the same time. Photodiodes have been integrated on TFT-matrix backplanes in order to demonstrate the concept in X-ray imagers.

Whole-slide imaging is a robust alternative to traditional fluorescent microscopy for fluorescence in situ hybridization imaging using break-apart DNA probes.

Science.gov (United States)

Laurent, Camille; Guérin, Maxime; Frenois, François-Xavier; Thuries, Valérie; Jalabert, Laurence; Brousset, Pierre; Valmary-Degano, Séverine

2013-08-01

Fluorescence in situ hybridization is an indispensable technique used in routine pathology and for theranostic purposes. Because fluorescence in situ hybridization techniques require sophisticated microscopic workstations and long procedures of image acquisition with sometimes subjective and poorly reproducible results, we decided to test a whole-slide imaging system as an alternative approach. In this study, we used the latest generation of Pannoramic 250 Flash digital microscopes (P250 Flash digital microscopes; 3DHISTECH, Budapest, Hungary) to digitize fluorescence in situ hybridization slides of diffuse large B cells lymphoma cases for detecting MYC rearrangement. The P250 Flash digital microscope was found to be precise with better definition of split signals in cells containing MYC rearrangement with fewer truncated signals as compared to traditional fluorescence microscopy. This digital technique is easier thanks to the preview function, which allows almost immediate identification of the tumor area, and the panning and zooming functionalities as well as a shorter acquisition time. Moreover, fluorescence in situ hybridization analyses using the digital technique appeared to be more reproducible between pathologists. Finally, the digital technique also allowed prolonged conservation of photos. In conclusion, whole-slide imaging technologies represent rapid, robust, and highly sensitive methods for interpreting fluorescence in situ hybridization slides with break-apart probes. In addition, these techniques offer an easier way to interpret the signals and allow definitive storage of the images for pathology expert networks or e-learning databases. Copyright © 2013 Elsevier Inc. All rights reserved.

Hello World Deep Learning in Medical Imaging.

Science.gov (United States)

Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

2018-05-03

There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

Use of mobile devices for medical imaging.

Science.gov (United States)

Hirschorn, David S; Choudhri, Asim F; Shih, George; Kim, Woojin

2014-12-01

Mobile devices have fundamentally changed personal computing, with many people forgoing the desktop and even laptop computer altogether in favor of a smaller, lighter, and cheaper device with a touch screen. Doctors and patients are beginning to expect medical images to be available on these devices for consultative viewing, if not actual diagnosis. However, this raises serious concerns with regard to the ability of existing mobile devices and networks to quickly and securely move these images. Medical images often come in large sets, which can bog down a network if not conveyed in an intelligent manner, and downloaded data on a mobile device are highly vulnerable to a breach of patient confidentiality should that device become lost or stolen. Some degree of regulation is needed to ensure that the software used to view these images allows all relevant medical information to be visible and manipulated in a clinically acceptable manner. There also needs to be a quality control mechanism to ensure that a device's display accurately conveys the image content without loss of contrast detail. Furthermore, not all mobile displays are appropriate for all types of images. The smaller displays of smart phones, for example, are not well suited for viewing entire chest radiographs, no matter how small and numerous the pixels of the display may be. All of these factors should be taken into account when deciding where, when, and how to use mobile devices for the display of medical images. Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.

NiftyNet: a deep-learning platform for medical imaging.

Science.gov (United States)

Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

2018-05-01

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new

Physics and engineering of medical imaging

International Nuclear Information System (INIS)

Guzzardi, R.

1987-01-01

The ever-growing development in the technology of Medical Imaging has a continuous and significant impact in the practice of Medicine as well as in the clinical research activity. The information and accuracy obtained by whatever imaging methodology is a complex result of a multidisciplinary effort of several sciences, such as Physics, Engineering, Electronics, Chemistry and Medicine. In this book, the state-of-the-art is described of the technology at the base of NMR, Ultrasound, X-ray CT, Nuclear Medicine, Positron Tomography and other Imaging Modalities such as Thermography or Biomagnetism, considering both the research and industrial point of view. For every imaging modality the most important clinical applications are described, together with the delineation of problems and future needs. Furthermore, specific sections of the book are devoted to general aspects of Medical Imaging, such as Reconstruction Techniques, 2-D and 3-D Display, Quality Control, Archiving, Market Trends and Correlative Assessment. (Auth.)

Data Analysis Strategies in Medical Imaging.

Science.gov (United States)

Parmar, Chintan; Barry, Joseph D; Hosny, Ahmed; Quackenbush, John; Aerts, Hugo Jwl

2018-03-26

Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence (AI) has allowed for detailed quantification of radiographic characteristics of tissues using predefined engineered algorithms or deep learning methods. Precedents in radiology as well as a wealth of research studies hint at the clinical relevance of these characteristics. However, there are critical challenges associated with the analysis of medical imaging data. While some of these challenges are specific to the imaging field, many others like reproducibility and batch effects are generic and have already been addressed in other quantitative fields such as genomics. Here, we identify these pitfalls and provide recommendations for analysis strategies of medical imaging data including data normalization, development of robust models, and rigorous statistical analyses. Adhering to these recommendations will not only improve analysis quality, but will also enhance precision medicine by allowing better integration of imaging data with other biomedical data sources. Copyright ©2018, American Association for Cancer Research.

Medical image transmission via communication satellite: evaluation of ultrasonographic images.

Science.gov (United States)

Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S

1996-01-01

As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.

Energy functionals for medical image segmentation: choices and consequences

OpenAIRE

McIntosh, Christopher

2011-01-01

Medical imaging continues to permeate the practice of medicine, but automated yet accurate segmentation and labeling of anatomical structures continues to be a major obstacle to computerized medical image analysis. Though there exists numerous approaches for medical image segmentation, one in particular has gained increasing popularity: energy minimization-based techniques, and the large set of methods encompassed therein. With these techniques an energy function must be chosen, segmentations...

Novel medical image enhancement algorithms

Science.gov (United States)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Gadgetron: An Open Source Framework for Medical Image Reconstruction

DEFF Research Database (Denmark)

Hansen, Michael Schacht; Sørensen, Thomas Sangild

2013-01-01

This work presents a new open source framework for medical image reconstruction called the “Gadgetron.” The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or “Gadgets” from raw data to reconstructed images...... with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its...

An open architecture for medical image workstation

Science.gov (United States)

Liang, Liang; Hu, Zhiqiang; Wang, Xiangyun

2005-04-01

Dealing with the difficulties of integrating various medical image viewing and processing technologies with a variety of clinical and departmental information systems and, in the meantime, overcoming the performance constraints in transferring and processing large-scale and ever-increasing image data in healthcare enterprise, we design and implement a flexible, usable and high-performance architecture for medical image workstations. This architecture is not developed for radiology only, but for any workstations in any application environments that may need medical image retrieving, viewing, and post-processing. This architecture contains an infrastructure named Memory PACS and different kinds of image applications built on it. The Memory PACS is in charge of image data caching, pre-fetching and management. It provides image applications with a high speed image data access and a very reliable DICOM network I/O. In dealing with the image applications, we use dynamic component technology to separate the performance-constrained modules from the flexibility-constrained modules so that different image viewing or processing technologies can be developed and maintained independently. We also develop a weakly coupled collaboration service, through which these image applications can communicate with each other or with third party applications. We applied this architecture in developing our product line and it works well. In our clinical sites, this architecture is applied not only in Radiology Department, but also in Ultrasonic, Surgery, Clinics, and Consultation Center. Giving that each concerned department has its particular requirements and business routines along with the facts that they all have different image processing technologies and image display devices, our workstations are still able to maintain high performance and high usability.

47 CFR 15.513 - Technical requirements for medical imaging systems.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 1 2010-10-01 2010-10-01 false Technical requirements for medical imaging... DEVICES Ultra-Wideband Operation § 15.513 Technical requirements for medical imaging systems. (a) The UWB... MHz and 10,600 MHz. (b) Operation under the provisions of this section is limited to medical imaging...

Quantitative imaging features: extension of the oncology medical image database

Science.gov (United States)

Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

2015-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

CERN manufactured hybrid photon detectors

CERN Multimedia

Maximilien Brice

2004-01-01

These hybrid photon detectors (HPDs) produce an electric signal from a single photon. An electron is liberated from a photocathode and accelerated to a silicon pixel array allowing the location of the photon on the cathode to be recorded. The electronics and optics for these devices have been developed in close collaboration with industry. HPDs have potential for further use in astrophysics and medical imaging.

Use of medical imaging as an epidemiologic tracer

International Nuclear Information System (INIS)

Dartigues, J.F.

1987-01-01

Medical imaging is a source of data for clinical and epidemiological research just like any other factual information obtained during medical treatment. Medical imaging data, like any other information, are not really useful unless they are obtained in rigorously controlled and determined conditions, defined a priori in the research protocol. In order to be use as an epidemiologic tracer (that is, as a meaning of finding a given pathology in a given population and during a given time period), the imaging data have to be valid, reliable, and representative, of easy access and obtained at a low cost [fr

Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

Science.gov (United States)

Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

2014-01-01

Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

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Guanqiu Qi

2017-10-01

Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

Performance analysis of AES-Blowfish hybrid algorithm for security of patient medical record data

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Mahmud H, Amir; Angga W, Bayu; Tommy; Marwan E, Andi; Siregar, Rosyidah

2018-04-01

A file security is one method to protect data confidentiality, integrity and information security. Cryptography is one of techniques used to secure and guarantee data confidentiality by doing conversion to the plaintext (original message) to cipher text (hidden message) with two important processes, they are encrypt and decrypt. Some researchers proposed a hybrid method to improve data security. In this research we proposed hybrid method of AES-blowfish (BF) to secure the patient’s medical report data into the form PDF file that sources from database. Generation method of private and public key uses two ways of approach, those are RSA method f RSA and ECC. We will analyze impact of these two ways of approach for hybrid method at AES-blowfish based on time and Throughput. Based on testing results, BF method is faster than AES and AES-BF hybrid, however AES-BF hybrid is better for throughput compared with AES and BF is higher.

A cloud collaborative medical image platform oriented by social network

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Muniz, Frederico B.; Araújo, Luciano V.; Nunes, Fátima L. S.

2017-03-01

Computer-aided diagnosis systems using medical images and three-dimensional models as input data have greatly expanded and developed, but in terms of building suitable image databases to assess them, the challenge remains. Although there are some image databases available for this purpose, they are generally limited to certain types of exams or contain a limited number of medical cases. The objective of this work is to present the concepts and the development of a collaborative platform for sharing medical images and three-dimensional models, providing a resource to share and increase the number of images available for researchers. The collaborative cloud platform, called CATALYZER, aims to increase the availability and sharing of graphic objects, including 3D images, and their reports that are essential for research related to medical images. A survey conducted with researchers and health professionals indicated that this could be an innovative approach in the creation of medical image databases, providing a wider variety of cases together with a considerable amount of shared information among its users.

Imaging of RNA in situ hybridization by atomic force microscopy

NARCIS (Netherlands)

Kalle, W.H.J.; Macville, M.V.E.; van de Corput, M.P.C.; de Grooth, B.G.; Tanke, H.J.; Raap, A.K.

In this study we investigated the possibility of imaging internal cellular molecules after cytochemical detection with atomic force microscopy (AFM). To this end, rat 9G and HeLa cells were hybridized with haptenized probes for 28S ribosomal RNA, human elongation factor mRNA and cytomegalovirus

Real-time image mosaicing for medical applications.

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Loewke, Kevin E; Camarillo, David B; Jobst, Christopher A; Salisbury, J Kenneth

2007-01-01

In this paper we describe the development of a robotically-assisted image mosaicing system for medical applications. The processing occurs in real-time due to a fast initial image alignment provided by robotic position sensing. Near-field imaging, defined by relatively large camera motion, requires translations as well as pan and tilt orientations to be measured. To capture these measurements we use 5-d.o.f. sensing along with a hand-eye calibration to account for sensor offset. This sensor-based approach speeds up the mosaicing, eliminates cumulative errors, and readily handles arbitrary camera motions. Our results have produced visually satisfactory mosaics on a dental model but can be extended to other medical images.

RNA Imaging with Multiplexed Error Robust Fluorescence in situ Hybridization

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Moffitt, Jeffrey R.; Zhuang, Xiaowei

2016-01-01

Quantitative measurements of both the copy number and spatial distribution of large fractions of the transcriptome in single-cells could revolutionize our understanding of a variety of cellular and tissue behaviors in both healthy and diseased states. Single-molecule Fluorescence In Situ Hybridization (smFISH)—an approach where individual RNAs are labeled with fluorescent probes and imaged in their native cellular and tissue context—provides both the copy number and spatial context of RNAs but has been limited in the number of RNA species that can be measured simultaneously. Here we describe Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH), a massively parallelized form of smFISH that can image and identify hundreds to thousands of different RNA species simultaneously with high accuracy in individual cells in their native spatial context. We provide detailed protocols on all aspects of MERFISH, including probe design, data collection, and data analysis to allow interested laboratories to perform MERFISH measurements themselves. PMID:27241748

Use of organoboranes in modern medical imaging

International Nuclear Information System (INIS)

Kabalka, G.W.

1991-01-01

Isotopically labeled materials have proven to be invaluable in chemical, medical, and biological research. Organoboranes are beginning to play a significant role in the synthesis of medically important materials which contain both stable and short-lived isotopes. The organic compounds of boron possess characteristics which make them ideal intermediates in radiopharmaceutical pathways; these include the facts that boron reactions tolerate a wide variety of physiologically active functionality and that the reactions proceed rapidly and in high yields. Boranes have found important applications in modern medical imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI). (author)

Image processing for medical diagnosis using CNN

International Nuclear Information System (INIS)

Arena, Paolo; Basile, Adriano; Bucolo, Maide; Fortuna, Luigi

2003-01-01

Medical diagnosis is one of the most important area in which image processing procedures are usefully applied. Image processing is an important phase in order to improve the accuracy both for diagnosis procedure and for surgical operation. One of these fields is tumor/cancer detection by using Microarray analysis. The research studies in the Cancer Genetics Branch are mainly involved in a range of experiments including the identification of inherited mutations predisposing family members to malignant melanoma, prostate and breast cancer. In bio-medical field the real-time processing is very important, but often image processing is a quite time-consuming phase. Therefore techniques able to speed up the elaboration play an important rule. From this point of view, in this work a novel approach to image processing has been developed. The new idea is to use the Cellular Neural Networks to investigate on diagnostic images, like: Magnetic Resonance Imaging, Computed Tomography, and fluorescent cDNA microarray images

Present and future of the hybrid imaging method SPECT/CT

International Nuclear Information System (INIS)

Kostadinova, I.

2013-01-01

Full text: Introduction: Based on the data in the literature and on our 4 year clinical experience applied for the first time in our country hybrid imaging - single photon emission tomography combined with computed tomography (SPECT / CT) it is clear that to obtain comprehensive information about the function and structure of the studied organ; the time for the diagnosis and thus the start of adequate treatment become shorter. The resulting scintigraphic image is with better quality due to CT correction of ‘diffusion’ gamma radiation, which leads to greater diagnostic accuracy. What you will learn: complex imaging method is used mainly in the field of endocrinology, cardiology, oncology, orthopedics, pulmology, neurology, and neurosurgery. It can be prove a given disease by visualization and localization of the organ lesions and determine the stage of the tumor process, to plan the type of subsequent treatment, to follow the effects of the therapy, and to predict the effect of an interventional or miniinvasive surgical procedure. Discussion: The result of the application of the hybrid imaging method is a change in the interpretation of more than half of the studied patients and in the treatment in more than a quarter of them. Conclusion: The clinical indications for SPECT/CT, and evidence of increased diagnostic accuracy compared with self- administered scintigraphic or CT methods are continuous expanded

A Hybrid 2D/3D User Interface for Radiological Diagnosis.

Science.gov (United States)

Mandalika, Veera Bhadra Harish; Chernoglazov, Alexander I; Billinghurst, Mark; Bartneck, Christoph; Hurrell, Michael A; Ruiter, Niels de; Butler, Anthony P H; Butler, Philip H

2018-02-01

This paper presents a novel 2D/3D desktop virtual reality hybrid user interface for radiology that focuses on improving 3D manipulation required in some diagnostic tasks. An evaluation of our system revealed that our hybrid interface is more efficient for novice users and more accurate for both novice and experienced users when compared to traditional 2D only interfaces. This is a significant finding because it indicates, as the techniques mature, that hybrid interfaces can provide significant benefit to image evaluation. Our hybrid system combines a zSpace stereoscopic display with 2D displays, and mouse and keyboard input. It allows the use of 2D and 3D components interchangeably, or simultaneously. The system was evaluated against a 2D only interface with a user study that involved performing a scoliosis diagnosis task. There were two user groups: medical students and radiology residents. We found improvements in completion time for medical students, and in accuracy for both groups. In particular, the accuracy of medical students improved to match that of the residents.

Multi-channel medical imaging system

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Frangioni, John V

2013-12-31

A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remain in the subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may provide an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide used to capture images. The system may be configured for use in open surgical procedures by providing an operating area that is closed to ambient light. The systems described herein provide two or more diagnostic imaging channels for capture of multiple, concurrent diagnostic images and may be used where a visible light image may be usefully supplemented by two or more images that are independently marked for functional interest.

FUZZY BASED CONTRAST STRETCHING FOR MEDICAL IMAGE ENHANCEMENT

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T.C. Raja Kumar

2011-07-01

Full Text Available Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and the fuzzy set is determined from the position of the input image pixel. The result indicates the good performance of the proposed fuzzy based stretching. The inverse transform of the real values are mapped with the input image to generate the fuzzy statistics. This approach gives a flexible image enhancement for medical images in the presence of noises.

An intelligent framework for medical image retrieval using MDCT and multi SVM.

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Balan, J A Alex Rajju; Rajan, S Edward

2014-01-01

Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

Multi-Wave and Hybrid Imaging Techniques: A New Direction for Nondestructive Testing and Structural Health Monitoring

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Yuhua Cheng

2013-11-01

Full Text Available In this article, the state-of-the-art multi-wave and hybrid imaging techniques in the field of nondestructive evaluation and structural health monitoring were comprehensively reviewed. A new direction for assessment and health monitoring of various structures by capitalizing the advantages of those imaging methods was discussed. Although sharing similar system configurations, the imaging physics and principles of multi-wave phenomena and hybrid imaging methods are inherently different. After a brief introduction of nondestructive evaluation (NDE , structure health monitoring (SHM and their related challenges, several recent advances that have significantly extended imaging methods from laboratory development into practical applications were summarized, followed by conclusions and discussion on future directions.

Machine Learning in Medical Imaging.

Science.gov (United States)

Giger, Maryellen L

2018-03-01

Advances in both imaging and computers have synergistically led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks, such as risk assessment, detection, diagnosis, prognosis, and therapy response, as well as in multi-omics disease discovery. A brief overview of the field is given here, allowing the reader to recognize the terminology, the various subfields, and components of machine learning, as well as the clinical potential. Radiomics, an expansion of computer-aided diagnosis, has been defined as the conversion of images to minable data. The ultimate benefit of quantitative radiomics is to (1) yield predictive image-based phenotypes of disease for precision medicine or (2) yield quantitative image-based phenotypes for data mining with other -omics for discovery (ie, imaging genomics). For deep learning in radiology to succeed, note that well-annotated large data sets are needed since deep networks are complex, computer software and hardware are evolving constantly, and subtle differences in disease states are more difficult to perceive than differences in everyday objects. In the future, machine learning in radiology is expected to have a substantial clinical impact with imaging examinations being routinely obtained in clinical practice, providing an opportunity to improve decision support in medical image interpretation. The term of note is decision support, indicating that computers will augment human decision making, making it more effective and efficient. The clinical impact of having computers in the routine clinical practice may allow radiologists to further integrate their knowledge with their clinical colleagues in other medical specialties and allow for precision medicine. Copyright © 2018. Published by Elsevier Inc.

Aliphatic polyesters for medical imaging and theranostic applications.

Science.gov (United States)

Nottelet, Benjamin; Darcos, Vincent; Coudane, Jean

2015-11-01

Medical imaging is a cornerstone of modern medicine. In that context the development of innovative imaging systems combining biomaterials and contrast agents (CAs)/imaging probes (IPs) for improved diagnostic and theranostic applications focuses intense research efforts. In particular, the classical aliphatic (co)polyesters poly(lactide) (PLA), poly(lactide-co-glycolide) (PLGA) and poly(ɛ-caprolactone) (PCL), attract much attention due to their long track record in the medical field. This review aims therefore at providing a state-of-the-art of polyester-based imaging systems. In a first section a rapid description of the various imaging modalities, including magnetic resonance imaging (MRI), optical imaging, computed tomography (CT), ultrasound (US) and radionuclide imaging (SPECT, PET) will be given. Then, the two main strategies used to combine the CAs/IPs and the polyesters will be discussed. In more detail we will first present the strategies relying on CAs/IPs encapsulation in nanoparticles, micelles, dendrimers or capsules. We will then present chemical modifications of polyesters backbones and/or polyester surfaces to yield macromolecular imaging agents. Finally, opportunities offered by these innovative systems will be illustrated with some recent examples in the fields of cell labeling, diagnostic or theranostic applications and medical devices. Copyright © 2015 Elsevier B.V. All rights reserved.

Brain medical image diagnosis based on corners with importance-values.

Science.gov (United States)

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection

Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

Directory of Open Access Journals (Sweden)

Mehdi Hussain

2016-05-01

Full Text Available The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR with an adaptive least significant bit (ALSB is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns and higher texture (asymmetry patterns areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images are conducted with recent least significant bit (LSB-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR.

Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

Science.gov (United States)

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

Visualization index for image-enabled medical records

Science.gov (United States)

Dong, Wenjie; Zheng, Weilin; Sun, Jianyong; Zhang, Jianguo

2011-03-01

With the widely use of healthcare information technology in hospitals, the patients' medical records are more and more complex. To transform the text- or image-based medical information into easily understandable and acceptable form for human, we designed and developed an innovation indexing method which can be used to assign an anatomical 3D structure object to every patient visually to store indexes of the patients' basic information, historical examined image information and RIS report information. When a doctor wants to review patient historical records, he or she can first load the anatomical structure object and the view the 3D index of this object using a digital human model tool kit. This prototype system helps doctors to easily and visually obtain the complete historical healthcare status of patients, including large amounts of medical data, and quickly locate detailed information, including both reports and images, from medical information systems. In this way, doctors can save time that may be better used to understand information, obtain a more comprehensive understanding of their patients' situations, and provide better healthcare services to patients.

Aligning Islamic Spirituality to Medical Imaging.

Science.gov (United States)

Zainuddin, Zainul Ibrahim

2017-10-01

This paper attempts to conceptualize Islamic spirituality in medical imaging that deals with the humanistic and technical dimensions. It begins with establishing an understanding concerning spirituality, an area that now accepted as part of patient-centred care. This is followed by discussions pertaining to Islamic spirituality, related to the practitioner, patient care and the practice. Possible avenues towards applying Islamic spirituality in medical imaging are proposed. It is hoped that the resultant harmonization between Islamic spirituality and the practice will trigger awareness and interests pertaining to the role of a Muslim practitioner in advocating and enhancing Islamic spirituality.

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study.

Directory of Open Access Journals (Sweden)

Oliver S Grosser

Full Text Available Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT or positron emission tomography (PET with computed tomography (CT. Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR on the image quality of the low-dose CT images.Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88 and the contrast-to-noise ratio (CNR was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04. In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001.In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.

An Improved FCM Medical Image Segmentation Algorithm Based on MMTD

Directory of Open Access Journals (Sweden)

Ningning Zhou

2014-01-01

Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.

Organization and visualization of medical images in radiotherapy

International Nuclear Information System (INIS)

Lorang, T.

2001-05-01

In modern radiotherapy, various imaging equipment is used to acquire views from inside human bodies. Tomographic imaging equipment is acquiring stacks of cross-sectional images, software implementations derive three-dimensional volumes from planar images to allow for visualization of reconstructed cross-sections at any orientation and location and higher-level visualization systems allow for transparent views and surface rendering. Of upcoming interest in radiotherapy is mutual information, the integration of information from multiple imaging equipment res. from the same imaging equipment at different time stamps and varying acquisition parameters. Huge amounts of images are acquired nowadays at radiotherapy centers, requiring organization of images with respect to patient, acquisition and equipment to allow for visualization of images in a comparative and integrative manner. Especially for integration of image information from different equipment, geometrical information is required to allow for registration of images res. volumes. DICOM 3.0 has been introduced as a standard for information interchange with respect to medical imaging. Geometric information of cross-sections, demographic information of patients and medical information of acquisitions and equipment are covered by this standard, allowing for a high-level automation with respect to organization and visualization of medical images. Reconstructing cross-sectional images from volumes at any orientation and location is required for the purpose of registration and multi-planar views. Resampling and addressing of discrete volume data need be implemented efficiently to allow for simultaneous visualization of multiple cross-sectional images, especially with respect to multiple, non-isotropy volume data sets. (author)

A hybrid optical system for broadband imaging in guidance and control

Science.gov (United States)

Wu, Xiaofang; Jiang, Yuesong; Shen, Chunyan; Zhao, Yiming

2006-11-01

A binary optics method has been adopted to improve upon a conventional optical system in guidance and control, and a hybrid broadband imaging system that includes a binary surface is analyzed and evaluated by optical design software ZEMAX. The practical design shows that the introduction of binary optics can simplify the structure of the imaging system and reduce the size and weight of the broadband guidance and control system. Moreover, it can help to acquire images of radiation of different wavelengths from targets; hence it will result in improved overall performance of missiles in wars.

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)

The Handbook of Medical Image Perception and Techniques

Science.gov (United States)

Samei, Ehsan; Krupinski, Elizabeth

2014-07-01

1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and

Medical images storage using discrete cosine transform

International Nuclear Information System (INIS)

Arhouma, Ali M.; Ajaal, Tawfik; Marghani, Khaled

2010-01-01

The advances in technology during the last decades have made the use of digital images as one of the common things in everyday life. While the application of digital images in communicating information is very important, the cost of storing and transmitting images is much larger compared to storage and transmission of text. The main problem with all of the images was the fact that they take large size of memory space, large transmission bandwidth and long transmission time. Image data compression is needed to reduce the storage space,transmission bandwidth and transmission time. Medical image compression plays a key role as hospitals move towards filmless imaging and go completely digital. Image compression allows Picture Archiving and Communication Systems (PACS) to reduce the file size on their storage requirements while maintaining relevant diagnostic information. The reduced image file size yield reduced transmission times. Even as the capacity of storage media continues to increase, it is expected that the volume of uncompressed data produced by hospitals will exceed capacity of storage and drive up costs. This paper proposes a Discrete Cosine Transform (DCT) algorithm which can help to solve the image storage and transmission time problem in hospitals. Discrete cosine transform (DCT) has become the most popular technique for image compression over the past several years. One of the major reasons for its popularity is its selection as the standard for JPEG. DCTs are most commonly used for non-analytical applications such as image processing and digital signal-processing (DSP) applications such as video conferencing, fax systems, video disks, and high-definition television HDTV. They also can be used on a matrix of practically any dimension. The proposed (DCT) algorithm improves the performance of medical image compression while satisfying both the medical image quality, and the high compression ratio. Application of DCT coding algorithm to actual still images

Medical imaging and augmented reality. Proceedings

International Nuclear Information System (INIS)

Yang Guang-Zhong; Jiang Tianzi; Shen Dinggang; Gu Lixu; Yang Jie

2006-01-01

This book constitutes the refereed proceedings of the Third International Workshop on Medical Imaging and Augmented Reality, MIAR 2006, held in Shanghai, China, in August 2006. The 45 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on shape modeling and morphometry, patient specific modeling and quantification, surgical simulation and skills assessment, surgical guidance and navigation, image registration, PET image reconstruction, and image segmentation. (orig.)

Adaptive Beamforming for Medical Ultrasound Imaging

DEFF Research Database (Denmark)

Holfort, Iben Kraglund

This dissertation investigates the application of adaptive beamforming for medical ultrasound imaging. The investigations have been concentrated primarily on the Minimum Variance (MV) beamformer. A broadband implementation of theMV beamformer is described, and simulated data have been used...... to demonstrate the performance. The MV beamformer has been applied to different sets of ultrasound imaging sequences; synthetic aperture ultrasound imaging and plane wave ultrasound imaging. And an approach for applying MV optimized apodization weights on both the transmitting and the receiving apertures...

[Managing digital medical imaging projects in healthcare services: lessons learned].

Science.gov (United States)

Rojas de la Escalera, D

2013-01-01

Medical imaging is one of the most important diagnostic instruments in clinical practice. The technological development of digital medical imaging has enabled healthcare services to undertake large scale projects that require the participation and collaboration of many professionals of varied backgrounds and interests as well as substantial investments in infrastructures. Rather than focusing on systems for dealing with digital medical images, this article deals with the management of projects for implementing these systems, reviewing various organizational, technological, and human factors that are critical to ensure the success of these projects and to guarantee the compatibility and integration of digital medical imaging systems with other health information systems. To this end, the author relates several lessons learned from a review of the literature and the author's own experience in the technical coordination of digital medical imaging projects. Copyright © 2012 SERAM. Published by Elsevier Espana. All rights reserved.

Diagnostic information management system for the evaluation of medical images

Energy Technology Data Exchange (ETDEWEB)

Higa, Toshiaki; Torizuka, Kanji; Minato, Kotaro; Komori, Masaru; Hirakawa, Akina

1985-04-01

A practical, small and low-cost diagnostic information management system has been developed for a comparative study of various medical imaging procedures, including ordinary radiography, X-ray computed tomography, emission computed tomography, and so forth. The purpose of the system is to effectively manage the original image data files and diagnostic descriptions during the various imaging procedures. A diagnostic description of each imaging procedure for each patient is made on a hand-sort punched-card with line-drawings and ordinary medical terminology and then coded and computerized using Index for Roentgen Diagnoses (American College of Radiology). A database management software (DB Master) on a personal computer (Apple II) is used for searching for patients' records on hand-sort punched-cards and finally original medical images. Discussed are realistic use of medical images and an effective form of diagnostic descriptions.

Diagnostic information management system for the evaluation of medical images

International Nuclear Information System (INIS)

Higa, Toshiaki; Torizuka, Kanji; Minato, Kotaro; Komori, Masaru; Hirakawa, Akina.

1985-01-01

A practical, small and low-cost diagnostic information management system has been developed for a comparative study of various medical imaging procedures, including ordinary radiography, X-ray computed tomography, emission computed tomography, and so forth. The purpose of the system is to effectively manage the original image data files and diagnostic descriptions during the various imaging procedures. A diagnostic description of each imaging procedure for each patient is made on a hand-sort punched-card with line-drawings and ordinary medical terminology and then coded and computerized using Index for Roentgen Diagnoses (American College of Radiology). A database management software (DB Master) on a personal computer (Apple II) is used for searching for patients' records on hand-sort punched-cards and finally original medical images. Discussed are realistic use of medical images and an effective form of diagnostic descriptions. (author)

Microwave imaging for conducting scatterers by hybrid particle swarm optimization with simulated annealing

International Nuclear Information System (INIS)

Mhamdi, B.; Grayaa, K.; Aguili, T.

2011-01-01

In this paper, a microwave imaging technique for reconstructing the shape of two-dimensional perfectly conducting scatterers by means of a stochastic optimization approach is investigated. Based on the boundary condition and the measured scattered field derived by transverse magnetic illuminations, a set of nonlinear integral equations is obtained and the imaging problem is reformulated in to an optimization problem. A hybrid approximation algorithm, called PSO-SA, is developed in this work to solve the scattering inverse problem. In the hybrid algorithm, particle swarm optimization (PSO) combines global search and local search for finding the optimal results assignment with reasonable time and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The hybrid approach elegantly combines the exploration ability of PSO with the exploitation ability of SA. Reconstruction results are compared with exact shapes of some conducting cylinders; and good agreements with the original shapes are observed.

Intelligent medical image processing by simulated annealing

International Nuclear Information System (INIS)

Ohyama, Nagaaki

1992-01-01

Image processing is being widely used in the medical field and already has become very important, especially when used for image reconstruction purposes. In this paper, it is shown that image processing can be classified into 4 categories; passive, active, intelligent and visual image processing. These 4 classes are explained at first through the use of several examples. The results show that the passive image processing does not give better results than the others. Intelligent image processing, then, is addressed, and the simulated annealing method is introduced. Due to the flexibility of the simulated annealing, formulated intelligence is shown to be easily introduced in an image reconstruction problem. As a practical example, 3D blood vessel reconstruction from a small number of projections, which is insufficient for conventional method to give good reconstruction, is proposed, and computer simulation clearly shows the effectiveness of simulated annealing method. Prior to the conclusion, medical file systems such as IS and C (Image Save and Carry) is pointed out to have potential for formulating knowledge, which is indispensable for intelligent image processing. This paper concludes by summarizing the advantages of simulated annealing. (author)

Identifying regions of interest in medical images using self-organizing maps.

Science.gov (United States)

Teng, Wei-Guang; Chang, Ping-Lin

2012-10-01

Advances in data acquisition, processing and visualization techniques have had a tremendous impact on medical imaging in recent years. However, the interpretation of medical images is still almost always performed by radiologists. Developments in artificial intelligence and image processing have shown the increasingly great potential of computer-aided diagnosis (CAD). Nevertheless, it has remained challenging to develop a general approach to process various commonly used types of medical images (e.g., X-ray, MRI, and ultrasound images). To facilitate diagnosis, we recommend the use of image segmentation to discover regions of interest (ROI) using self-organizing maps (SOM). We devise a two-stage SOM approach that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions. In addition, by appropriately conducting the recursive merging steps to merge smaller regions into larger ones, radiologists can usually identify one or more ROIs within a medical image.

Machine learning approaches in medical image analysis

DEFF Research Database (Denmark)

de Bruijne, Marleen

2016-01-01

Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

Hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic imaging

Science.gov (United States)

Chen, Zhenyue; Deán-Ben, Xosé Luís.; Gottschalk, Sven; Razansky, Daniel

2018-02-01

Fluorescence imaging is widely employed in all fields of cell and molecular biology due to its high sensitivity, high contrast and ease of implementation. However, the low spatial resolution and lack of depth information, especially in strongly-scattering samples, restrict its applicability for deep-tissue imaging applications. On the other hand, optoacoustic imaging is known to deliver a unique set of capabilities such as high spatial and temporal resolution in three dimensions, deep penetration and spectrally-enriched imaging contrast. Since fluorescent substances can generate contrast in both modalities, simultaneous fluorescence and optoacoustic readings can provide new capabilities for functional and molecular imaging of living organisms. Optoacoustic images can further serve as valuable anatomical references based on endogenous hemoglobin contrast. Herein, we propose a hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic tomography, both operating in reflection mode, which synergistically combines the advantages of stand-alone systems. Validation of the spatial resolution and sensitivity of the system were first carried out in tissue mimicking phantoms while in vivo imaging was further demonstrated by tracking perfusion of an optical contrast agent in a mouse brain in the hybrid imaging mode. Experimental results show that the proposed system effectively exploits the contrast mechanisms of both imaging modalities, making it especially useful for accurate monitoring of fluorescence-based signal dynamics in highly scattering samples.

Wavelet optimization for content-based image retrieval in medical databases.

Science.gov (United States)

Quellec, G; Lamard, M; Cazuguel, G; Cochener, B; Roux, C

2010-04-01

We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize the distribution of wavelet coefficients in each subband of the decomposition. A distance measure is then defined to compare two image signatures and thus retrieve the most similar images in a database when a query image is submitted by a physician. To retrieve relevant images from a medical database, the signatures and the distance measure must be related to the medical interpretation of images. As a consequence, we introduce several degrees of freedom in the system so that it can be tuned to any pathology and image modality. In particular, we propose to adapt the wavelet basis, within the lifting scheme framework, and to use a custom decomposition scheme. Weights are also introduced between subbands. All these parameters are tuned by an optimization procedure, using the medical grading of each image in the database to define a performance measure. The system is assessed on two medical image databases: one for diabetic retinopathy follow up and one for screening mammography, as well as a general purpose database. Results are promising: a mean precision of 56.50%, 70.91% and 96.10% is achieved for these three databases, when five images are returned by the system. Copyright 2009 Elsevier B.V. All rights reserved.

ImageParser: a tool for finite element generation from three-dimensional medical images

Directory of Open Access Journals (Sweden)

Yamada T

2004-10-01

Full Text Available Abstract Background The finite element method (FEM is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures of interest (ROIs may be irregular and fuzzy. Methods A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. Results The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. Conclusion The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information.

Improved Software to Browse the Serial Medical Images for Learning.

Science.gov (United States)

Kwon, Koojoo; Chung, Min Suk; Park, Jin Seo; Shin, Byeong Seok; Chung, Beom Sun

2017-07-01

The thousands of serial images used for medical pedagogy cannot be included in a printed book; they also cannot be efficiently handled by ordinary image viewer software. The purpose of this study was to provide browsing software to grasp serial medical images efficiently. The primary function of the newly programmed software was to select images using 3 types of interfaces: buttons or a horizontal scroll bar, a vertical scroll bar, and a checkbox. The secondary function was to show the names of the structures that had been outlined on the images. To confirm the functions of the software, 3 different types of image data of cadavers (sectioned and outlined images, volume models of the stomach, and photos of the dissected knees) were inputted. The browsing software was downloadable for free from the homepage (anatomy.co.kr) and available off-line. The data sets provided could be replaced by any developers for their educational achievements. We anticipate that the software will contribute to medical education by allowing users to browse a variety of images. © 2017 The Korean Academy of Medical Sciences.

FAST: framework for heterogeneous medical image computing and visualization.

Science.gov (United States)

Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank

2015-11-01

Computer systems are becoming increasingly heterogeneous in the sense that they consist of different processors, such as multi-core CPUs and graphic processing units. As the amount of medical image data increases, it is crucial to exploit the computational power of these processors. However, this is currently difficult due to several factors, such as driver errors, processor differences, and the need for low-level memory handling. This paper presents a novel FrAmework for heterogeneouS medical image compuTing and visualization (FAST). The framework aims to make it easier to simultaneously process and visualize medical images efficiently on heterogeneous systems. FAST uses common image processing programming paradigms and hides the details of memory handling from the user, while enabling the use of all processors and cores on a system. The framework is open-source, cross-platform and available online. Code examples and performance measurements are presented to show the simplicity and efficiency of FAST. The results are compared to the insight toolkit (ITK) and the visualization toolkit (VTK) and show that the presented framework is faster with up to 20 times speedup on several common medical imaging algorithms. FAST enables efficient medical image computing and visualization on heterogeneous systems. Code examples and performance evaluations have demonstrated that the toolkit is both easy to use and performs better than existing frameworks, such as ITK and VTK.

Introduction to Medical Image Analysis

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

This book is a result of a collaboration between DTU Informatics at the Technical University of Denmark and the Laboratory of Computer Vision and Media Technology at Aalborg University. It is partly based on the book ”Image and Video Processing”, second edition by Thomas Moeslund. The aim...... of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

A Survey on Deep Learning in Medical Image Analysis

NARCIS (Netherlands)

Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.

2017-01-01

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

Noise removal for medical X-ray images in wavelet domain

International Nuclear Information System (INIS)

Wang, Ling; Lu, Jianming; Li, Yeqiu; Yahagi, Takashi; Okamoto, Takahide

2006-01-01

Many important problems in engineering and science are well-modeled by Poisson noise, the noise of medical X-ray image is Poisson noise. In this paper, we propose a method of noise removal for degraded medical X-ray image using improved preprocessing and improved BayesShrink (IBS) method in wavelet domain. Firstly, we pre-process the medical X-ray image, Secondly, we apply the Daubechies (db) wavelet transform to medical X-ray image to acquire scaling and wavelet coefficients. Thirdly, we apply the proposed IBS method to process wavelet coefficients. Finally, we compute the inverse wavelet transform for the thresholded coefficeints. Experimental results show that the proposed method always outperforms traditional methods. (author)

Cascaded Window Memoization for Medical Imaging

OpenAIRE

Khalvati , Farzad; Kianpour , Mehdi; Tizhoosh , Hamid ,

2011-01-01

Part 12: Medical Applications of ANN and Ethics of AI; International audience; Window Memoization is a performance improvement technique for image processing algorithms. It is based on removing computational redundancy in an algorithm applied to a single image, which is inherited from data redundancy in the image. The technique employs a fuzzy reuse mechanism to eliminate unnecessary computations. This paper extends the window memoization technique such that in addition to exploiting the data...

New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Zeng, Tieyong

2013-01-01

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

A list of image files of planarians analyzed by in situ hybridication and immunohistochemical staining - Plabrain DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Plabrain DB A list of image files of planarians analyzed by in situ hybridication and immunohistochemical...tu hybridication and also protein distribution by immunohistochemical staining in intact planarians or plana...planarians analyzed by In situ hybridication and immunohistochemical staining . D..._image#en Data acquisition method Whole-mount in situ hybridication, immunohistochemical...te Policy | Contact Us A list of image files of planarians analyzed by in situ hybridication and immunohistochemical staining - Plabrain DB | LSDB Archive ...

elastix: a toolbox for intensity-based medical image registration.

Science.gov (United States)

Klein, Stefan; Staring, Marius; Murphy, Keelin; Viergever, Max A; Pluim, Josien P W

2010-01-01

Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.

Rapid development of medical imaging tools with open-source libraries.

Science.gov (United States)

Caban, Jesus J; Joshi, Alark; Nagy, Paul

2007-11-01

Rapid prototyping is an important element in researching new imaging analysis techniques and developing custom medical applications. In the last ten years, the open source community and the number of open source libraries and freely available frameworks for biomedical research have grown significantly. What they offer are now considered standards in medical image analysis, computer-aided diagnosis, and medical visualization. A cursory review of the peer-reviewed literature in imaging informatics (indeed, in almost any information technology-dependent scientific discipline) indicates the current reliance on open source libraries to accelerate development and validation of processes and techniques. In this survey paper, we review and compare a few of the most successful open source libraries and frameworks for medical application development. Our dual intentions are to provide evidence that these approaches already constitute a vital and essential part of medical image analysis, diagnosis, and visualization and to motivate the reader to use open source libraries and software for rapid prototyping of medical applications and tools.

Imaging Hybrid Photon Detectors with a Reflective Photocathode

CERN Document Server

Ferenc, D

2000-01-01

Modern epitaxially grown photocathodes, like GaAsP, bring a very high inherent quantum efficiency, but are rather expensive due to the complicated manufacturing and mounting process. We argue that such photocathodes could be used in reflective mode, in order to avoid the risky and expensive removal of the epitaxial growth substrate. Besides that the quantum efficiency should increase considerably. In this paper we present results of the development of large imaging Hybrid Photon Detectors (HPDs), particularly designed for such reflective photocathodes.

Mathematics and computer science in medical imaging

International Nuclear Information System (INIS)

Viergever, M.A.; Todd-Pokroper, A.E.

1987-01-01

The book is divided into two parts. Part 1 gives an introduction to and an overview of the field in ten tutorial chapters. Part 2 contains a selection of invited and proffered papers reporting on current research. Subjects covered in depth are: analytical image reconstruction, regularization, iterative methods, image structure, 3-D display, compression, architectures for image processing, statistical pattern recognition, and expert systems in medical imaging

Medical imaging technology reviews and computational applications

CERN Document Server

Dewi, Dyah

2015-01-01

This book presents the latest research findings and reviews in the field of medical imaging technology, covering ultrasound diagnostics approaches for detecting osteoarthritis, breast carcinoma and cardiovascular conditions, image guided biopsy and segmentation techniques for detecting lung cancer, image fusion, and simulating fluid flows for cardiovascular applications. It offers a useful guide for students, lecturers and professional researchers in the fields of biomedical engineering and image processing.

Object-oriented design of medical imaging software.

Science.gov (United States)

Ligier, Y; Ratib, O; Logean, M; Girard, C; Perrier, R; Scherrer, J R

1994-01-01

A special software package for interactive display and manipulation of medical images was developed at the University Hospital of Geneva, as part of a hospital wide Picture Archiving and Communication System (PACS). This software package, called Osiris, was especially designed to be easily usable and adaptable to the needs of noncomputer-oriented physicians. The Osiris software has been developed to allow the visualization of medical images obtained from any imaging modality. It provides generic manipulation tools, processing tools, and analysis tools more specific to clinical applications. This software, based on an object-oriented paradigm, is portable and extensible. Osiris is available on two different operating systems: the Unix X-11/OSF-Motif based workstations, and the Macintosh family.

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)

Near-infrared spectroscopic tissue imaging for medical applications

Science.gov (United States)

Demos, Stavros [Livermore, CA; Staggs, Michael C [Tracy, CA

2006-12-12

Near infrared imaging using elastic light scattering and tissue autofluorescence are explored for medical applications. The approach involves imaging using cross-polarized elastic light scattering and tissue autofluorescence in the Near Infra-Red (NIR) coupled with image processing and inter-image operations to differentiate human tissue components.

APES Beamforming Applied to Medical Ultrasound Imaging

DEFF Research Database (Denmark)

Blomberg, Ann E. A.; Holfort, Iben Kraglund; Austeng, Andreas

2009-01-01

Recently, adaptive beamformers have been introduced to medical ultrasound imaging. The primary focus has been on the minimum variance (MV) (or Capon) beamformer. This work investigates an alternative but closely related beamformer, the Amplitude and Phase Estimation (APES) beamformer. APES offers...... added robustness at the expense of a slightly lower resolution. The purpose of this study was to evaluate the performance of the APES beamformer on medical imaging data, since correct amplitude estimation often is just as important as spatial resolution. In our simulations we have used a 3.5 MHz, 96...... element linear transducer array. When imaging two closely spaced point targets, APES displays nearly the same resolution as the MV, and at the same time improved amplitude control. When imaging cysts in speckle, APES offers speckle statistics similar to that of the DAS, without the need for temporal...

Automatic Image Alignment and Stitching of Medical Images with Seam Blending

OpenAIRE

Abhinav Kumar; Raja Sekhar Bandaru; B Madhusudan Rao; Saket Kulkarni; Nilesh Ghatpande

2010-01-01

This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together usin...

Organic-inorganic hybrid carbon dots for cell imaging

Science.gov (United States)

Liu, Huan; Zhang, Hongwen; Li, Jiayu; Tang, Yuying; Cao, Yu; Jiang, Yan

2018-04-01

In this paper, nitrogen-doped carbon dots (CDs) had been synthesized directly by one-step ultrasonic treatment under mild conditions. During the functionalization process, Octa-aminopropyl polyhedral oligomeric silsesquioxane hydrochloride salt (OA-POSS) was used as stabilizing and passivation agent, which lead to self-assembling of CDs in aqueous medium solution. OA-POSS was obtained via hydrolytic condensation of γ-aminopropyl triethoxy silane (APTES). The average size of CDs prepared was approximately 3.3 nm with distribution between 2.5 nm and 4.5 nm. The prepared organic-inorganic hybrid carbon dots have several characteristics such as photoluminescence emission wavelength, efficient cellular uptake, and good biocompatibility. The results indicate that OA-POSS can maintain the fluorescence properties of the carbon dots effectively, and reduced cytotoxicity provides the possibility for biomedical applications. More than 89% of the Hela cells were viable when incubated with 2 mg ml‑1 or lesser organic-inorganic hybrid carbon dots. Thus, it provides a potential for multicolor imaging with HeLa cells.

Motion correction in medical imaging.

OpenAIRE

Smith, Rhodri

2017-01-01

It is estimated that over half of current adults within Great Britain under the age of 65 will be diagnosed with cancer at some point in their lifetime. Medical Imaging forms an essential part of cancer clinical protocols and is able to furnish morphological, metabolic and functional information. The imaging of molecular interactions of biological processes in vivo with Positron Emission Tomography (PET) is informative not only for disease detection but also therapeutic response. The qualitat...

Development of gamma-photon/Cerenkov-light hybrid system for simultaneous imaging of I-131 radionuclide

Energy Technology Data Exchange (ETDEWEB)

Yamamoto, Seiichi; Suzuki, Mayumi; Kato, Katsuhiko [Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine (Japan); Watabe, Tadashi; Ikeda, Hayato; Kanai, Yasukazu [Department of Molecular Imaging in Medicine, Osaka University Graduate School of Medicine (Japan); Ogata, Yoshimune [Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine (Japan); Hatazawa, Jun [Department of Molecular Imaging in Medicine, Osaka University Graduate School of Medicine (Japan)

2016-09-11

Although iodine 131 (I-131) is used for radionuclide therapy, high resolution images are difficult to obtain with conventional gamma cameras because of the high energy of I-131 gamma photons (364 keV). Cerenkov-light imaging is a possible method for beta emitting radionuclides, and I-131 (606 MeV maximum beta energy) is a candidate to obtain high resolution images. We developed a high energy gamma camera system for I-131 radionuclide and combined it with a Cerenkov-light imaging system to form a gamma-photon/Cerenkov-light hybrid imaging system to compare the simultaneously measured images of these two modalities. The high energy gamma imaging detector used 0.85-mm×0.85-mm×10-mm thick GAGG scintillator pixels arranged in a 44×44 matrix with a 0.1-mm thick reflector and optical coupled to a Hamamatsu 2 in. square position sensitive photomultiplier tube (PSPMT: H12700 MOD). The gamma imaging detector was encased in a 2 cm thick tungsten shield, and a pinhole collimator was mounted on its top to form a gamma camera system. The Cerenkov-light imaging system was made of a high sensitivity cooled CCD camera. The Cerenkov-light imaging system was combined with the gamma camera using optical mirrors to image the same area of the subject. With this configuration, we simultaneously imaged the gamma photons and the Cerenkov-light from I-131 in the subjects. The spatial resolution and sensitivity of the gamma camera system for I-131 were respectively ~3 mm FWHM and ~10 cps/MBq for the high sensitivity collimator at 10 cm from the collimator surface. The spatial resolution of the Cerenkov-light imaging system was 0.64 mm FWHM at 10 cm from the system surface. Thyroid phantom and rat images were successfully obtained with the developed gamma-photon/Cerenkov-light hybrid imaging system, allowing direct comparison of these two modalities. Our developed gamma-photon/Cerenkov-light hybrid imaging system will be useful to evaluate the advantages and disadvantages of these two

Elastix : a toolbox for intensity-based medical image registration

NARCIS (Netherlands)

Klein, S.; Staring, M.; Murphy, K.; Viergever, M.A.; Pluim, J.P.W.

2010-01-01

Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of

Hybrid protein-inorganic nanoparticles: From tumor-targeted drug delivery to cancer imaging.

Science.gov (United States)

Elzoghby, Ahmed O; Hemasa, Ayman L; Freag, May S

2016-12-10

Recently, a great interest has been paid to the development of hybrid protein-inorganic nanoparticles (NPs) for drug delivery and cancer diagnostics in order to combine the merits of both inorganic and protein nanocarriers. This review primarily discusses the most outstanding advances in the applications of the hybrids of naturally-occurring proteins with iron oxide, gadolinium, gold, silica, calcium phosphate NPs, carbon nanotubes, and quantum dots in drug delivery and cancer imaging. Various strategies that have been utilized for the preparation of protein-functionalized inorganic NPs and the mechanisms involved in the drug loading process are discussed. How can the protein functionalization overcome the limitations of colloidal stability, poor dispersibility and toxicity associated with inorganic NPs is also investigated. Moreover, issues relating to the influence of protein hybridization on the cellular uptake, tumor targeting efficiency, systemic circulation, mucosal penetration and skin permeation of inorganic NPs are highlighted. A special emphasis is devoted to the novel approaches utilizing the protein-inorganic nanohybrids in combined cancer therapy, tumor imaging, and theranostic applications as well as stimuli-responsive drug release from the nanohybrids. Copyright © 2016 Elsevier B.V. All rights reserved.

Medical physics personnel for medical imaging: requirements, conditions of involvement and staffing levels-French recommendations

International Nuclear Information System (INIS)

Isambert, Aurelie; Valero, Marc; Rousse, Carole; Blanchard, Vincent; Le Du, Dominique; Guilhem, Marie-Therese; Dieudonne, Arnaud; Pierrat, Noelle; Salvat, Cecile

2015-01-01

The French regulations concerning the involvement of medical physicists in medical imaging procedures are relatively vague. In May 2013, the ASN and the SFPM issued recommendations regarding Medical Physics Personnel for Medical Imaging: Requirements, Conditions of Involvement and Staffing Levels. In these recommendations, the various areas of activity of medical physicists in radiology and nuclear medicine have been identified and described, and the time required to perform each task has been evaluated. Criteria for defining medical physics staffing levels are thus proposed. These criteria are defined according to the technical platform, the procedures and techniques practised on it, the number of patients treated and the number of persons in the medical and paramedical teams requiring periodic training. The result of this work is an aid available to each medical establishment to determine their own needs in terms of medical physics. (authors)

Hybrid coded aperture and Compton imaging using an active mask

International Nuclear Information System (INIS)

Schultz, L.J.; Wallace, M.S.; Galassi, M.C.; Hoover, A.S.; Mocko, M.; Palmer, D.M.; Tornga, S.R.; Kippen, R.M.; Hynes, M.V.; Toolin, M.J.; Harris, B.; McElroy, J.E.; Wakeford, D.; Lanza, R.C.; Horn, B.K.P.; Wehe, D.K.

2009-01-01

The trimodal imager (TMI) images gamma-ray sources from a mobile platform using both coded aperture (CA) and Compton imaging (CI) modalities. In this paper we will discuss development and performance of image reconstruction algorithms for the TMI. In order to develop algorithms in parallel with detector hardware we are using a GEANT4 [J. Allison, K. Amako, J. Apostolakis, H. Araujo, P.A. Dubois, M. Asai, G. Barrand, R. Capra, S. Chauvie, R. Chytracek, G. Cirrone, G. Cooperman, G. Cosmo, G. Cuttone, G. Daquino, et al., IEEE Trans. Nucl. Sci. NS-53 (1) (2006) 270] based simulation package to produce realistic data sets for code development. The simulation code incorporates detailed detector modeling, contributions from natural background radiation, and validation of simulation results against measured data. Maximum likelihood algorithms for both imaging methods are discussed, as well as a hybrid imaging algorithm wherein CA and CI information is fused to generate a higher fidelity reconstruction.

Imaging requirements for medical applications of additive manufacturing.

Science.gov (United States)

Huotilainen, Eero; Paloheimo, Markku; Salmi, Mika; Paloheimo, Kaija-Stiina; Björkstrand, Roy; Tuomi, Jukka; Markkola, Antti; Mäkitie, Antti

2014-02-01

Additive manufacturing (AM), formerly known as rapid prototyping, is steadily shifting its focus from industrial prototyping to medical applications as AM processes, bioadaptive materials, and medical imaging technologies develop, and the benefits of the techniques gain wider knowledge among clinicians. This article gives an overview of the main requirements for medical imaging affected by needs of AM, as well as provides a brief literature review from existing clinical cases concentrating especially on the kind of radiology they required. As an example application, a pair of CT images of the facial skull base was turned into 3D models in order to illustrate the significance of suitable imaging parameters. Additionally, the model was printed into a preoperative medical model with a popular AM device. Successful clinical cases of AM are recognized to rely heavily on efficient collaboration between various disciplines - notably operating surgeons, radiologists, and engineers. The single main requirement separating tangible model creation from traditional imaging objectives such as diagnostics and preoperative planning is the increased need for anatomical accuracy in all three spatial dimensions, but depending on the application, other specific requirements may be present as well. This article essentially intends to narrow the potential communication gap between radiologists and engineers who work with projects involving AM by showcasing the overlap between the two disciplines.

Segmentation of elongated structures in medical images

NARCIS (Netherlands)

Staal, Jozef Johannes

2004-01-01

The research described in this thesis concerns the automatic detection, recognition and segmentation of elongated structures in medical images. For this purpose techniques have been developed to detect subdimensional pointsets (e.g. ridges, edges) in images of arbitrary dimension. These

Challenges for data storage in medical imaging research.

Science.gov (United States)

Langer, Steve G

2011-04-01

Researchers in medical imaging have multiple challenges for storing, indexing, maintaining viability, and sharing their data. Addressing all these concerns requires a constellation of tools, but not all of them need to be local to the site. In particular, the data storage challenges faced by researchers can begin to require professional information technology skills. With limited human resources and funds, the medical imaging researcher may be better served with an outsourcing strategy for some management aspects. This paper outlines an approach to manage the main objectives faced by medical imaging scientists whose work includes processing and data mining on non-standard file formats, and relating those files to the their DICOM standard descendents. The capacity of the approach scales as the researcher's need grows by leveraging the on-demand provisioning ability of cloud computing.

The future of medical imaging

International Nuclear Information System (INIS)

Maidment, A. D. A.

2010-01-01

The organisers of this conference have kindly provided me with the forum to look forward and examine the future of medical imaging. My view of the future is informed by my own research directions; thus, I illustrate my vision of the future with results from my own research, and from the research that has motivated me over the last few years. As such, the results presented are specific to the field of breast imaging; however, I believe that the trends presented have general applicability, and hope that this discourse will motivate new research. My vision of the future can be summarised in accordance with three broad trends: (1) increased prevalence of low-dose tomographic X-ray imaging; (2) continuing advances in functional and molecular X-ray imaging; and (3) novel image-based bio-marker discovery. (authors)

Medical image reconstruction. A conceptual tutorial

International Nuclear Information System (INIS)

Zeng, Gengsheng Lawrence

2010-01-01

''Medical Image Reconstruction: A Conceptual Tutorial'' introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l 0 -minimization are also included. (orig.)

Medical image processing on the GPU - past, present and future.

Science.gov (United States)

Eklund, Anders; Dufort, Paul; Forsberg, Daniel; LaConte, Stephen M

2013-12-01

Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges. Copyright © 2013 Elsevier B.V. All rights reserved.

Statistical physics of medical ultrasonic images

International Nuclear Information System (INIS)

Wagner, R.F.; Insana, M.F.; Brown, D.G.; Smith, S.W.

1987-01-01

The physical and statistical properties of backscattered signals in medical ultrasonic imaging are reviewed in terms of: 1) the radiofrequency signal; 2) the envelope (video or magnitude) signal; and 3) the density of samples in simple and in compounded images. There is a wealth of physical information in backscattered signals in medical ultrasound. This information is contained in the radiofrequency spectrum - which is not typically displayed to the viewer - as well as in the higher statistical moments of the envelope or video signal - which are not readily accessed by the human viewer of typical B-scans. This information may be extracted from the detected backscattered signals by straightforward signal processing techniques at low resolution

Magnetic resonance imaging of the inner ear by using a hybrid radiofrequency coil at 7 T

Science.gov (United States)

Kim, Kyoung-Nam; Heo, Phil; Kim, Young-Bo; Han, Gyu-Cheol

2015-01-01

Visualization of the membranous structures of the inner ear has been limited to the detection of the normal fluid signal intensity within the bony labyrinth by using magnetic resonance imaging (MRI) equipped with a 1.5 Tesla (T) magnet. High-field (HF) MRI has been available for more than a decade, and numerous studies have documented its significant advantages over conventional MRI with regards to its use in basic scientific research and routine clinical assessments. No previous studies of the inner ear by using HF MRI have been reported, in part because high-quality resolution of mastoid pneumatization is challenging due to artifacts generated in the HF environment and insufficient performance of radiofrequency (RF) coils. Therefore, a hybrid RF coil with integrated circuitry was developed at 7 T and was targeted for anatomical imaging to achieve a high resolution image of the structure of the human inner ear, excluding the bony portion. The inner-ear's structure is composed of soft tissues containing hydrogen ions and includes the membranous labyrinth, endolymphatic space, perilymphatic space, and cochlear-vestibular nerves. Visualization of the inner-ear's anatomy was performed in-vivo with a custom-designed hybrid RF coil and a specific imaging protocol based on an interpolated breath-held examination sequence. The comparative signal intensity value at 30-mm away from the phantom side was 88% higher for the hybrid RF coil and 24% higher for the 8-channel transmit/receive (Tx/Rx) coil than for the commercial birdcage coil. The optimized MRI protocol employed a hybrid RF coil because it enabled high-resolution imaging of the inner-ear's anatomy and accurate mapping of structures including the cochlea and the semicircular canals. These results indicate that 7 T MRI achieves high spatial resolution visualization of the inner-ear's anatomy. Therefore, MRI imaging using a hybrid RF coil at 7 T could provide a powerful tool for clinical investigations of petrous

Bayesian image restoration for medical images using radon transform

International Nuclear Information System (INIS)

Shouno, Hayaru; Okada, Masato

2010-01-01

We propose an image reconstruction algorithm using Bayesian inference for Radon transformed observation data, which often appears in the field of medical image reconstruction known as computed tomography (CT). In order to apply our Bayesian reconstruction method, we introduced several hyper-parameters that control the ratio between prior information and the fidelity of the observation process. Since the quality of the reconstructed image is influenced by the estimation accuracy of these hyper-parameters, we propose an inference method for them based on the marginal likelihood maximization principle as well as the image reconstruction method. We are able to demonstrate a reconstruction result superior to that obtained using the conventional filtered back projection method. (author)

Medical Imaging Informatics: Towards a Personalized Computational Patient.

Science.gov (United States)

Ayache, N

2016-05-20

Medical Imaging Informatics has become a fast evolving discipline at the crossing of Informatics, Computational Sciences, and Medicine that is profoundly changing medical practices, for the patients' benefit.

Mesh Processing in Medical-Image Analysis-a Tutorial

DEFF Research Database (Denmark)

Levine, Joshua A.; Paulsen, Rasmus Reinhold; Zhang, Yongjie

2012-01-01

Medical-image analysis requires an understanding of sophisticated scanning modalities, constructing geometric models, building meshes to represent domains, and downstream biological applications. These four steps form an image-to-mesh pipeline. For research in this field to progress, the imaging...

[Current situations and problems of quality control for medical imaging display systems].

Science.gov (United States)

Shibutani, Takayuki; Setojima, Tsuyoshi; Ueda, Katsumi; Takada, Katsumi; Okuno, Teiichi; Onoguchi, Masahisa; Nakajima, Tadashi; Fujisawa, Ichiro

2015-04-01

Diagnostic imaging has been shifted rapidly from film to monitor diagnostic. Consequently, Japan medical imaging and radiological systems industries association (JIRA) have recommended methods of quality control (QC) for medical imaging display systems. However, in spite of its need by majority of people, executing rate is low. The purpose of this study was to validate the problem including check items about QC for medical imaging display systems. We performed acceptance test of medical imaging display monitors based on Japanese engineering standards of radiological apparatus (JESRA) X-0093*A-2005 to 2009, and performed constancy test based on JESRA X-0093*A-2010 from 2010 to 2012. Furthermore, we investigated the cause of trouble and repaired number. Medical imaging display monitors had 23 inappropriate monitors about visual estimation, and all these monitors were not criteria of JESRA about luminance uniformity. Max luminance was significantly lower year-by-year about measurement estimation, and the 29 monitors did not meet the criteria of JESRA about luminance deviation. Repaired number of medical imaging display monitors had 25, and the cause was failure liquid crystal panel. We suggested the problems about medical imaging display systems.

Superconductors and medical imaging

International Nuclear Information System (INIS)

Aubert, Guy

2011-01-01

After difficult beginnings in the 1970's, magnetic resonance imaging (MRI) has evolved to become nowadays the jewel in the crown of medical technology. Superconductors have been a key factor for the extraordinary expansion of MRI which in turn represents about 75 % of their total market. After recalling some basic principles, this article traces their common history and refers to future developments. (author)

User Oriented Platform for Data Analytics in Medical Imaging Repositories.

Science.gov (United States)

Valerio, Miguel; Godinho, Tiago Marques; Costa, Carlos

2016-01-01

The production of medical imaging studies and associated data has been growing in the last decades. Their primary use is to support medical diagnosis and treatment processes. However, the secondary use of the tremendous amount of stored data is generally more limited. Nowadays, medical imaging repositories have turned into rich databanks holding not only the images themselves, but also a wide range of metadata related to the medical practice. Exploring these repositories through data analysis and business intelligence techniques has the potential of increasing the efficiency and quality of the medical practice. Nevertheless, the continuous production of tremendous amounts of data makes their analysis difficult by conventional approaches. This article proposes a novel automated methodology to derive knowledge from medical imaging repositories that does not disrupt the regular medical practice. Our method is able to apply statistical analysis and business intelligence techniques directly on top of live institutional repositories. It is a Web-based solution that provides extensive dashboard capabilities, including complete charting and reporting options, combined with data mining components. Moreover, it enables the operator to set a wide multitude of query parameters and operators through the use of an intuitive graphical interface.

Intravascular ultrasonic-photoacoustic (IVUP) endoscope with 2.2-mm diameter catheter for medical imaging.

Science.gov (United States)

Bui, Nhat Quang; Hlaing, Kyu Kyu; Nguyen, Van Phuc; Nguyen, Trung Hau; Oh, Yun-Ok; Fan, Xiao Feng; Lee, Yong Wook; Nam, Seung Yun; Kang, Hyun Wook; Oh, Junghwan

2015-10-01

Intravascular ultrasound (IVUS) imaging is extremely important for detection and characterization of high-risk atherosclerotic plaques as well as gastrointestinal diseases. Recently, intravascular photoacoustic (IVPA) imaging has been used to differentiate the composition of biological tissues with high optical contrast and ultrasonic resolution. The combination of these imaging techniques could provide morphological information and molecular screening to characterize abnormal tissues, which would help physicians to ensure vital therapeutic value and prognostic significance for patients before commencing therapy. In this study, integration of a high-frequency IVUS imaging catheter (45MHz, single-element, unfocused, 0.7mm in diameter) with a multi-mode optical fiber (0.6mm in core diameter, 0.22 NA), an integrated intravascular ultrasonic-photoacoustic (IVUP) imaging catheter, was developed to provide spatial and functional information on light distribution in a turbid sample. Simultaneously, IVUS imaging was co-registered to IVPA imaging to construct 3D volumetric sample images. In a phantom study, a polyvinyl alcohol (PVA) tissue-mimicking arterial vessel phantom with indocyanine green (ICG) and methylene blue (MB) inclusion was used to demonstrate the feasibility of mapping the biological dyes, which are used in cardiovascular and cancer diagnostics. For the ex vivo study, an excised sample of pig intestine with ICG was utilized to target the biomarkers present in the gastrointestinal tumors or the atherosclerotic plaques with the proposed hybrid technique. The results indicated that IVUP endoscope with the 2.2-mm diameter catheter could be a useful tool for medical imaging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Diagnostic Medical Imaging in Pediatric Patients and Subsequent Cancer Risk.

Science.gov (United States)

Mulvihill, David J; Jhawar, Sachin; Kostis, John B; Goyal, Sharad

2017-11-01

The use of diagnostic medical imaging is becoming increasingly more commonplace in the pediatric setting. However, many medical imaging modalities expose pediatric patients to ionizing radiation, which has been shown to increase the risk of cancer development in later life. This review article provides a comprehensive overview of the available data regarding the risk of cancer development following exposure to ionizing radiation from diagnostic medical imaging. Attention is paid to modalities such as computed tomography scans and fluoroscopic procedures that can expose children to radiation doses orders of magnitude higher than standard diagnostic x-rays. Ongoing studies that seek to more precisely determine the relationship of diagnostic medical radiation in children and subsequent cancer development are discussed, as well as modern strategies to better quantify this risk. Finally, as cardiovascular imaging and intervention contribute substantially to medical radiation exposure, we discuss strategies to enhance radiation safety in these areas. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Multispectral system for medical fluorescence imaging

International Nuclear Information System (INIS)

Andersson, P.S.; Montan, S.; Svanberg, S.

1987-01-01

The principles of a powerful multicolor imaging system for tissue fluorescence diagnostics are discussed. Four individually spectrally filtered images are formed on a matrix detector by means of a split-mirror arrangement. The four images are processed in a computer, pixel by pixel, by means of mathematical operations, leading to an optimized contrast image, which enhances a selected feature. The system is being developed primarily for medical fluorescence imaging, but has wide applications in fluorescence, reflectance, and transmission monitoring related to a wide range of industrial and environmental problems. The system operation is described for the case of linear imaging on a diode array detector. Laser-induced fluorescence is used for cancer tumor and arteriosclerotic plaque demarcation using the contrast enhancement capabilities of this imaging system. Further examples of applications include fluorescing minerals and flames

Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

Science.gov (United States)

Handels, H; Ehrhardt, J

2009-01-01

Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or

[Research progress of multi-model medical image fusion and recognition].

Science.gov (United States)

Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

2013-10-01

Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

Synchrotrons and their applications in medical imaging and therapy

International Nuclear Information System (INIS)

Lewis, R.

2004-01-01

Full text: Australasia's first synchrotron is being built on the campus of Monash University near Melbourne. Is it of any relevance to the medical imaging and radiation therapy communities? The answer is an unequivocal yes. Synchrotrons overcome many of the problems with conventional X-ray sources and as a result make it possible to demonstrate extraordinary advances in both X-ray imaging and indeed in radio-therapy. Synchrotron imaging offers us a window into what is possible and the results are spectacular. Specific examples include lung images that reveal alveolar structure and computed tomography of single cells. For therapy treatments are being pioneered that seem to be effective on high grade gliomas. An overview of the status of medical applications using synchrotrons will be given and the proposed Australian medical imaging and therapy facilities will be described and some of the proposed research highlighted. Copyright (2004) Australasian College of Physical Scientists and Engineers in Medicine

76 FR 45402 - Advisory Committee; Medical Imaging Drugs Advisory Committee; Re-Establishment

Science.gov (United States)

2011-07-29

.... FDA-2010-N-0002] Advisory Committee; Medical Imaging Drugs Advisory Committee; Re- Establishment... (FDA) is announcing the re- establishment of the Medical Imaging Drugs Advisory Committee in FDA's Center for Drug Evaluation and Research. This rule amends the current language for the Medical Imaging...

High-performance method of morphological medical image processing

Directory of Open Access Journals (Sweden)

Ryabykh M. S.

2016-07-01

Full Text Available the article shows the implementation of grayscale morphology vHGW algorithm for selection borders in the medical image. Image processing is executed using OpenMP and NVIDIA CUDA technology for images with different resolution and different size of the structuring element.

Digital fluoroscopy: a new development in medical imaging

International Nuclear Information System (INIS)

Maher, K.P.; Malone, J.F.; Dublin Inst. of Technology

1986-01-01

Medical fluoroscopy is briefly reviewed and video-image digitization is described. Image processing requirements and image processors available for digital fluoroscopy are discussed in detail. Specific reference is made to an application of digital fluoroscopy in the imaging of blood-vessels. This application involves an image substraction technique which is referred to as digital subtraction angiography (DSA). A number of DSA images of relevance to the discussion are included. (author)

Coherent hybrid electromagnetic field imaging

Science.gov (United States)

Cooke, Bradly J [Jemez Springs, NM; Guenther, David C [Los Alamos, NM

2008-08-26

An apparatus and corresponding method for coherent hybrid electromagnetic field imaging of a target, where an energy source is used to generate a propagating electromagnetic beam, an electromagnetic beam splitting means to split the beam into two or more coherently matched beams of about equal amplitude, and where the spatial and temporal self-coherence between each two or more coherently matched beams is preserved. Two or more differential modulation means are employed to modulate each two or more coherently matched beams with a time-varying polarization, frequency, phase, and amplitude signal. An electromagnetic beam combining means is used to coherently combine said two or more coherently matched beams into a coherent electromagnetic beam. One or more electromagnetic beam controlling means are used for collimating, guiding, or focusing the coherent electromagnetic beam. One or more apertures are used for transmitting and receiving the coherent electromagnetic beam to and from the target. A receiver is used that is capable of square-law detection of the coherent electromagnetic beam. A waveform generator is used that is capable of generation and control of time-varying polarization, frequency, phase, or amplitude modulation waveforms and sequences. A means of synchronizing time varying waveform is used between the energy source and the receiver. Finally, a means of displaying the images created by the interaction of the coherent electromagnetic beam with target is employed.

Medical physics personnel for medical imaging: requirements, conditions of involvement and staffing levels-French recommendations.

Science.gov (United States)

Isambert, Aurélie; Le Du, Dominique; Valéro, Marc; Guilhem, Marie-Thérèse; Rousse, Carole; Dieudonné, Arnaud; Blanchard, Vincent; Pierrat, Noëlle; Salvat, Cécile

2015-04-01

The French regulations concerning the involvement of medical physicists in medical imaging procedures are relatively vague. In May 2013, the ASN and the SFPM issued recommendations regarding Medical Physics Personnel for Medical Imaging: Requirements, Conditions of Involvement and Staffing Levels. In these recommendations, the various areas of activity of medical physicists in radiology and nuclear medicine have been identified and described, and the time required to perform each task has been evaluated. Criteria for defining medical physics staffing levels are thus proposed. These criteria are defined according to the technical platform, the procedures and techniques practised on it, the number of patients treated and the number of persons in the medical and paramedical teams requiring periodic training. The result of this work is an aid available to each medical establishment to determine their own needs in terms of medical physics. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

In Vivo Deep Tissue Fluorescence and Magnetic Imaging Employing Hybrid Nanostructures.

Science.gov (United States)

Ortgies, Dirk H; de la Cueva, Leonor; Del Rosal, Blanca; Sanz-Rodríguez, Francisco; Fernández, Nuria; Iglesias-de la Cruz, M Carmen; Salas, Gorka; Cabrera, David; Teran, Francisco J; Jaque, Daniel; Martín Rodríguez, Emma

2016-01-20

Breakthroughs in nanotechnology have made it possible to integrate different nanoparticles in one single hybrid nanostructure (HNS), constituting multifunctional nanosized sensors, carriers, and probes with great potential in the life sciences. In addition, such nanostructures could also offer therapeutic capabilities to achieve a wider variety of multifunctionalities. In this work, the encapsulation of both magnetic and infrared emitting nanoparticles into a polymeric matrix leads to a magnetic-fluorescent HNS with multimodal magnetic-fluorescent imaging abilities. The magnetic-fluorescent HNS are capable of simultaneous magnetic resonance imaging and deep tissue infrared fluorescence imaging, overcoming the tissue penetration limits of classical visible-light based optical imaging as reported here in living mice. Additionally, their applicability for magnetic heating in potential hyperthermia treatments is assessed.

Medical image security using modified chaos-based cryptography approach

Science.gov (United States)

Talib Gatta, Methaq; Al-latief, Shahad Thamear Abd

2018-05-01

The progressive development in telecommunication and networking technologies have led to the increased popularity of telemedicine usage which involve storage and transfer of medical images and related information so security concern is emerged. This paper presents a method to provide the security to the medical images since its play a major role in people healthcare organizations. The main idea in this work based on the chaotic sequence in order to provide efficient encryption method that allows reconstructing the original image from the encrypted image with high quality and minimum distortion in its content and doesn’t effect in human treatment and diagnosing. Experimental results prove the efficiency of the proposed method using some of statistical measures and robust correlation between original image and decrypted image.

Spatio-Temporal Encoding in Medical Ultrasound Imaging

DEFF Research Database (Denmark)

Gran, Fredrik

2005-01-01

In this dissertation two methods for spatio-temporal encoding in medical ultrasound imaging are investigated. The first technique is based on a frequency division approach. Here, the available spectrum of the transducer is divided into a set of narrow bands. A waveform is designed for each band...... the signal to noise ratio and simultaneously the penetration depth so that the medical doctor can image deeper lying structures. The method is tested both experimentally and in simulation and has also evaluated for the purpose of blood flow estimation. The work presented is based on four papers which...

Population Pharmacokinetics of Tracers: A New Tool for Medical Imaging?

Science.gov (United States)

Gandia, Peggy; Jaudet, Cyril; Chatelut, Etienne; Concordet, Didier

2017-02-01

Positron emission tomography-computed tomography is a medical imaging method measuring the activity of a radiotracer chosen to accumulate in cancer cells. A recent trend of medical imaging analysis is to account for the radiotracer's pharmacokinetic properties at a voxel (three-dimensional-pixel) level to separate the different tissues. These analyses are closely linked to population pharmacokinetic-pharmacodynamic modelling. Kineticists possess the cultural background to improve medical imaging analysis. This article stresses the common points with population pharmacokinetics and highlights the methodological locks that need to be lifted.

A hybrid biomechanical intensity based deformable image registration of lung 4DCT

International Nuclear Information System (INIS)

Samavati, Navid; Velec, Michael; Brock, Kristy

2015-01-01

Deformable image registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions (IGI). IGI demands a highly accurate registration that maintains its accuracy across the entire region of interest. This work evaluates the improvement in accuracy and consistency by refining the results of Morfeus, a biomechanical model-based DIR algorithm.A hybrid DIR algorithm is proposed based on, a biomechanical model–based DIR algorithm and a refinement step based on a B-spline intensity-based algorithm. Inhale and exhale reconstructions of four-dimensional computed tomography (4DCT) lung images from 31 patients were initially registered using the biomechanical DIR by modeling contact surface between the lungs and the chest cavity. The resulting deformations were then refined using the intensity-based algorithm to reduce any residual uncertainties. Important parameters in the intensity-based algorithm, including grid spacing, number of pyramids, and regularization coefficient, were optimized on 10 randomly-chosen patients (out of 31). Target registration error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images after registration. For each patient a minimum of 30 points/lung were used.Grid spacing of 8 mm, 5 levels of grid pyramids, and regularization coefficient of 3.0 were found to provide optimal results on 10 randomly chosen patients. Overall the entire patient population (n = 31), the hybrid method resulted in mean ± SD (90th%) TRE of 1.5 ± 1.4 (2.9) mm compared to 3.1 ± 1.9 (5.6) using biomechanical DIR and 2.6 ± 2.5 (6.1) using intensity-based DIR alone.The proposed hybrid biomechanical modeling intensity based algorithm is a promising DIR technique which could be used in various IGI procedures. The current investigation shows the efficacy of this approach for the registration of 4DCT images of the lungs with average accuracy of 1.5�

PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

Directory of Open Access Journals (Sweden)

Xingxing Zhu

2018-05-01

Full Text Available Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR-based registration methods have attracted much attention recently. However, the existing SR methods cannot provide satisfactory registration accuracy due to the utilization of hand-designed features for structural representation. To address this problem, the structural representation method based on the improved version of the simple deep learning network named PCANet is proposed for medical image registration. In the proposed method, PCANet is firstly trained on numerous medical images to learn convolution kernels for this network. Then, a pair of input medical images to be registered is processed by the learned PCANet. The features extracted by various layers in the PCANet are fused to produce multilevel features. The structural representation images are constructed for two input images based on nonlinear transformation of these multilevel features. The Euclidean distance between structural representation images is calculated and used as the similarity metrics. The objective function defined by the similarity metrics is optimized by L-BFGS method to obtain parameters of the free-form deformation (FFD model. Extensive experiments on simulated and real multimodal image datasets show that compared with the state-of-the-art registration methods, such as modality-independent neighborhood descriptor (MIND, normalized mutual information (NMI, Weber local descriptor (WLD, and the sum of squared differences on entropy images (ESSD, the proposed method provides better registration performance in terms of target registration error (TRE and subjective human vision.

Integration of Medical Imaging Including Ultrasound into a New Clinical Anatomy Curriculum

Science.gov (United States)

Moscova, Michelle; Bryce, Deborah A.; Sindhusake, Doungkamol; Young, Noel

2015-01-01

In 2008 a new clinical anatomy curriculum with integrated medical imaging component was introduced into the University of Sydney Medical Program. Medical imaging used for teaching the new curriculum included normal radiography, MRI, CT scans, and ultrasound imaging. These techniques were incorporated into teaching over the first two years of the…

High accuracy FIONA-AFM hybrid imaging

International Nuclear Information System (INIS)

Fronczek, D.N.; Quammen, C.; Wang, H.; Kisker, C.; Superfine, R.; Taylor, R.; Erie, D.A.; Tessmer, I.

2011-01-01

Multi-protein complexes are ubiquitous and play essential roles in many biological mechanisms. Single molecule imaging techniques such as electron microscopy (EM) and atomic force microscopy (AFM) are powerful methods for characterizing the structural properties of multi-protein and multi-protein-DNA complexes. However, a significant limitation to these techniques is the ability to distinguish different proteins from one another. Here, we combine high resolution fluorescence microscopy and AFM (FIONA-AFM) to allow the identification of different proteins in such complexes. Using quantum dots as fiducial markers in addition to fluorescently labeled proteins, we are able to align fluorescence and AFM information to ≥8 nm accuracy. This accuracy is sufficient to identify individual fluorescently labeled proteins in most multi-protein complexes. We investigate the limitations of localization precision and accuracy in fluorescence and AFM images separately and their effects on the overall registration accuracy of FIONA-AFM hybrid images. This combination of the two orthogonal techniques (FIONA and AFM) opens a wide spectrum of possible applications to the study of protein interactions, because AFM can yield high resolution (5-10 nm) information about the conformational properties of multi-protein complexes and the fluorescence can indicate spatial relationships of the proteins in the complexes. -- Research highlights: → Integration of fluorescent signals in AFM topography with high (<10 nm) accuracy. → Investigation of limitations and quantitative analysis of fluorescence-AFM image registration using quantum dots. → Fluorescence center tracking and display as localization probability distributions in AFM topography (FIONA-AFM). → Application of FIONA-AFM to a biological sample containing damaged DNA and the DNA repair proteins UvrA and UvrB conjugated to quantum dots.

Quantification of heterogeneity observed in medical images

OpenAIRE

Brooks, Frank J; Grigsby, Perry W

2013-01-01

Background There has been much recent interest in the quantification of visually evident heterogeneity within functional grayscale medical images, such as those obtained via magnetic resonance or positron emission tomography. In the case of images of cancerous tumors, variations in grayscale intensity imply variations in crucial tumor biology. Despite these considerable clinical implications, there is as yet no standardized method for measuring the heterogeneity observed via these imaging mod...

Anomaly detection for medical images based on a one-class classification

Science.gov (United States)

Wei, Qi; Ren, Yinhao; Hou, Rui; Shi, Bibo; Lo, Joseph Y.; Carin, Lawrence

2018-02-01

Detecting an anomaly such as a malignant tumor or a nodule from medical images including mammogram, CT or PET images is still an ongoing research problem drawing a lot of attention with applications in medical diagnosis. A conventional way to address this is to learn a discriminative model using training datasets of negative and positive samples. The learned model can be used to classify a testing sample into a positive or negative class. However, in medical applications, the high unbalance between negative and positive samples poses a difficulty for learning algorithms, as they will be biased towards the majority group, i.e., the negative one. To address this imbalanced data issue as well as leverage the huge amount of negative samples, i.e., normal medical images, we propose to learn an unsupervised model to characterize the negative class. To make the learned model more flexible and extendable for medical images of different scales, we have designed an autoencoder based on a deep neural network to characterize the negative patches decomposed from large medical images. A testing image is decomposed into patches and then fed into the learned autoencoder to reconstruct these patches themselves. The reconstruction error of one patch is used to classify this patch into a binary class, i.e., a positive or a negative one, leading to a one-class classifier. The positive patches highlight the suspicious areas containing anomalies in a large medical image. The proposed method has been tested on InBreast dataset and achieves an AUC of 0.84. The main contribution of our work can be summarized as follows. 1) The proposed one-class learning requires only data from one class, i.e., the negative data; 2) The patch-based learning makes the proposed method scalable to images of different sizes and helps avoid the large scale problem for medical images; 3) The training of the proposed deep convolutional neural network (DCNN) based auto-encoder is fast and stable.

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.

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

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Badal, A [U.S. Food and Drug Administration (CDRH/OSEL), Silver Spring, MD (United States); Zbijewski, W [Johns Hopkins University, Baltimore, MD (United States); Bolch, W [University of Florida, Gainesville, FL (United States); Sechopoulos, I [Emory University, Atlanta, GA (United States)

2014-06-15

virtual generation of medical images and accurate estimation of radiation dose and other imaging parameters. For this, detailed computational phantoms of the patient anatomy must be utilized and implemented within the radiation transport code. Computational phantoms presently come in one of three format types, and in one of four morphometric categories. Format types include stylized (mathematical equation-based), voxel (segmented CT/MR images), and hybrid (NURBS and polygon mesh surfaces). Morphometric categories include reference (small library of phantoms by age at 50th height/weight percentile), patient-dependent (larger library of phantoms at various combinations of height/weight percentiles), patient-sculpted (phantoms altered to match the patient's unique outer body contour), and finally, patient-specific (an exact representation of the patient with respect to both body contour and internal anatomy). The existence and availability of these phantoms represents a very important advance for the simulation of realistic medical imaging applications using Monte Carlo methods. New Monte Carlo simulation codes need to be thoroughly validated before they can be used to perform novel research. Ideally, the validation process would involve comparison of results with those of an experimental measurement, but accurate replication of experimental conditions can be very challenging. It is very common to validate new Monte Carlo simulations by replicating previously published simulation results of similar experiments. This process, however, is commonly problematic due to the lack of sufficient information in the published reports of previous work so as to be able to replicate the simulation in detail. To aid in this process, the AAPM Task Group 195 prepared a report in which six different imaging research experiments commonly performed using Monte Carlo simulations are described and their results provided. The simulation conditions of all six cases are provided in full detail

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

International Nuclear Information System (INIS)

Badal, A; Zbijewski, W; Bolch, W; Sechopoulos, I

2014-01-01

generation of medical images and accurate estimation of radiation dose and other imaging parameters. For this, detailed computational phantoms of the patient anatomy must be utilized and implemented within the radiation transport code. Computational phantoms presently come in one of three format types, and in one of four morphometric categories. Format types include stylized (mathematical equation-based), voxel (segmented CT/MR images), and hybrid (NURBS and polygon mesh surfaces). Morphometric categories include reference (small library of phantoms by age at 50th height/weight percentile), patient-dependent (larger library of phantoms at various combinations of height/weight percentiles), patient-sculpted (phantoms altered to match the patient's unique outer body contour), and finally, patient-specific (an exact representation of the patient with respect to both body contour and internal anatomy). The existence and availability of these phantoms represents a very important advance for the simulation of realistic medical imaging applications using Monte Carlo methods. New Monte Carlo simulation codes need to be thoroughly validated before they can be used to perform novel research. Ideally, the validation process would involve comparison of results with those of an experimental measurement, but accurate replication of experimental conditions can be very challenging. It is very common to validate new Monte Carlo simulations by replicating previously published simulation results of similar experiments. This process, however, is commonly problematic due to the lack of sufficient information in the published reports of previous work so as to be able to replicate the simulation in detail. To aid in this process, the AAPM Task Group 195 prepared a report in which six different imaging research experiments commonly performed using Monte Carlo simulations are described and their results provided. The simulation conditions of all six cases are provided in full detail, with all

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

Science.gov (United States)

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall

Intrasubject registration for change analysis in medical imaging

NARCIS (Netherlands)

Staring, M.

2008-01-01

Image matching is important for the comparison of medical images. Comparison is of clinical relevance for the analysis of differences due to changes in the health of a patient. For example, when a disease is imaged at two time points, then one wants to know if it is stable, has regressed, or

An evaluation on CT image acquisition method for medical VR applications

Science.gov (United States)

Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang

2017-02-01

Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.

Nonlinear spatial mode imaging of hybrid photonic crystal fibers

DEFF Research Database (Denmark)

Petersen, Sidsel Rübner; Alkeskjold, Thomas Tanggaard; Laurila, Marko

2013-01-01

Degenerate spontaneous four wave mixing is studied for the rst time in a large mode area hybrid photonic crystal ber, where light con nement is achieved by combined index- and bandgap guiding. Four wave mixing products are generated on the edges of the bandgaps, which is veri ed by numerical and ...... and experimental results. Since the core mode is in resonance with cladding modes near the bandedges an unconventional measurement technique is used, in this work named nonlinear spatial mode imaging....

A similarity-based data warehousing environment for medical images.

Science.gov (United States)

Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

2015-11-01

A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Medical imaging informatics simulators: a tutorial.

Science.gov (United States)

Huang, H K; Deshpande, Ruchi; Documet, Jorge; Le, Anh H; Lee, Jasper; Ma, Kevin; Liu, Brent J

2014-05-01

A medical imaging informatics infrastructure (MIII) platform is an organized method of selecting tools and synthesizing data from HIS/RIS/PACS/ePR systems with the aim of developing an imaging-based diagnosis or treatment system. Evaluation and analysis of these systems can be made more efficient by designing and implementing imaging informatics simulators. This tutorial introduces the MIII platform and provides the definition of treatment/diagnosis systems, while primarily focusing on the development of the related simulators. A medical imaging informatics (MII) simulator in this context is defined as a system integration of many selected imaging and data components from the MIII platform and clinical treatment protocols, which can be used to simulate patient workflow and data flow starting from diagnostic procedures to the completion of treatment. In these processes, DICOM and HL-7 standards, IHE workflow profiles, and Web-based tools are emphasized. From the information collected in the database of a specific simulator, evidence-based medicine can be hypothesized to choose and integrate optimal clinical decision support components. Other relevant, selected clinical resources in addition to data and tools from the HIS/RIS/PACS and ePRs platform may also be tailored to develop the simulator. These resources can include image content indexing, 3D rendering with visualization, data grid and cloud computing, computer-aided diagnosis (CAD) methods, specialized image-assisted surgical, and radiation therapy technologies. Five simulators will be discussed in this tutorial. The PACS-ePR simulator with image distribution is the cradle of the other simulators. It supplies the necessary PACS-based ingredients and data security for the development of four other simulators: the data grid simulator for molecular imaging, CAD-PACS, radiation therapy simulator, and image-assisted surgery simulator. The purpose and benefits of each simulator with respect to its clinical relevance

Shaping the future through innovations: From medical imaging to precision medicine.

Science.gov (United States)

Comaniciu, Dorin; Engel, Klaus; Georgescu, Bogdan; Mansi, Tommaso

2016-10-01

Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing precision medicine into clinical practice. This manuscript describes recently developed technologies for better handling of image information: photorealistic visualization of medical images with Cinematic Rendering, artificial agents for in-depth image understanding, support for minimally invasive procedures, and patient-specific computational models with enhanced predictive power. Throughout the manuscript we will analyze the capabilities of such technologies and extrapolate on their potential impact to advance the quality of medical care, while reducing its cost. Copyright © 2016 Elsevier B.V. All rights reserved.

Unsupervised segmentation of medical image based on difference of mutual information

Institute of Scientific and Technical Information of China (English)

L(U) Qingwen; CHEN Wufan

2006-01-01

In the scope of medical image processing, segmentation is important and difficult. There are still two problems which trouble us in this field. One is how to determine the number of clusters in an image and the other is how to segment medical images containing lesions. A new segmentation method called DDC, based on difference of mutual information (dMI) and pixon, is proposed in this paper. Experiments demonstrate that dMI shows one kind of intrinsic relationship between the segmented image and the original one and so it can be used to well determine the number of clusters. Furthermore, multi-modality medical images with lesions can be automatically and successfully segmented by DDC method.

Trends in the Use of Medical Imaging to Diagnose Appendicitis at an Academic Medical Center.

Science.gov (United States)

Repplinger, Michael D; Weber, Andrew C; Pickhardt, Perry J; Rajamanickam, Victoria P; Svenson, James E; Ehlenbach, William J; Westergaard, Ryan P; Reeder, Scott B; Jacobs, Elizabeth A

2016-09-01

To quantify the trends in imaging use for the diagnosis of appendicitis. A retrospective study covering a 22-year period was conducted at an academic medical center. Patients were identified by International Classification of Diseases-9 diagnosis code for appendicitis. Medical record data extraction of these patients included imaging test used (ultrasound, CT, or MRI), gender, age, and body mass index (BMI). The proportion of patients undergoing each scan was calculated by year. Regression analysis was performed to determine whether age, gender, or BMI affected imaging choice. The study included a total of 2,108 patients, including 967 (43.5%) females and 599 (27%) children (imaging used for the diagnosis of appendicitis decreased over time (P medical center, CT use increased more than 20-fold. However, no statistically significant trend was found for increased use of ultrasound or MRI. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Biocompatible multi-walled carbon nanotube–CdTe quantum dot–polymer hybrids for medical applications

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Baslak, Canan, E-mail: cananbaslak@gmail.com [Advanced Technology Research and Application Center, Selcuk University, 42075 Konya (Turkey); Department of Chemistry, Faculty of Science, Selcuk University, 42075 Konya (Turkey); Demirel Kars, Meltem, E-mail: dmeltem@yahoo.com [Advanced Technology Research and Application Center, Selcuk University, 42075 Konya (Turkey); Sarayonu Vocational High School, Selcuk University, 42430 Konya (Turkey); Karaman, Mustafa; Kus, Mahmut [Advanced Technology Research and Application Center, Selcuk University, 42075 Konya (Turkey); Department of Chemical Engineering, Faculty of Engineering, Selcuk University, 42075 Konya (Turkey); Cengeloglu, Yunus; Ersoz, Mustafa [Advanced Technology Research and Application Center, Selcuk University, 42075 Konya (Turkey); Department of Chemistry, Faculty of Science, Selcuk University, 42075 Konya (Turkey)

2015-04-15

Herein we report the synthesis of polymer coated quantum dots (QDs)–carbon nanotube composite material with high biocompatibility and low cellular toxicity. The synthesized multi-walled carbon nanotube (MWCNT)–QD-(-poly(glycidyl methacrylate)) (pGMA) hybrids were characterized using X-ray photoelectron spectroscopy, laser scanning confocal microscopy, transmission electron microscopy and scanning electron microscopy. The results showed that quantum dots were well-distributed on nanotube surfaces in high density. The toxicological assessments of QDs and MWCNT–QD–polymer hybrids in human mammary carcinoma cells and their fluorescence imaging in living cell system were carried out. MWCNT–QD–polymer hybrids possess intense red fluorescence signal under confocal microscopy and good fluorescence stability over 6-h exposure in living cell system. The toxicity comparison of QDs and MWCNT–QD–polymer hybrids has shown that the existence of PGMA thin coating on MWCNT–QD hybrid surface decreased the cellular toxicity and increased biocompatibility. - Highlights: • We report that polymer coating of QDs on CNTs increased their biocompatibility by decreasing cellular toxicity. • QD–CNT polymer hybrid material may be proposed as a good diagnostic agent to visualize cancer cells which may be improved as a therapeutic carrier in future. • Coating QDs with polymer seems to be a right choice to be used in medicinal applications both for diagnosis and for therapy.

Biocompatible multi-walled carbon nanotube–CdTe quantum dot–polymer hybrids for medical applications

International Nuclear Information System (INIS)

Baslak, Canan; Demirel Kars, Meltem; Karaman, Mustafa; Kus, Mahmut; Cengeloglu, Yunus; Ersoz, Mustafa

2015-01-01

Herein we report the synthesis of polymer coated quantum dots (QDs)–carbon nanotube composite material with high biocompatibility and low cellular toxicity. The synthesized multi-walled carbon nanotube (MWCNT)–QD-(-poly(glycidyl methacrylate)) (pGMA) hybrids were characterized using X-ray photoelectron spectroscopy, laser scanning confocal microscopy, transmission electron microscopy and scanning electron microscopy. The results showed that quantum dots were well-distributed on nanotube surfaces in high density. The toxicological assessments of QDs and MWCNT–QD–polymer hybrids in human mammary carcinoma cells and their fluorescence imaging in living cell system were carried out. MWCNT–QD–polymer hybrids possess intense red fluorescence signal under confocal microscopy and good fluorescence stability over 6-h exposure in living cell system. The toxicity comparison of QDs and MWCNT–QD–polymer hybrids has shown that the existence of PGMA thin coating on MWCNT–QD hybrid surface decreased the cellular toxicity and increased biocompatibility. - Highlights: • We report that polymer coating of QDs on CNTs increased their biocompatibility by decreasing cellular toxicity. • QD–CNT polymer hybrid material may be proposed as a good diagnostic agent to visualize cancer cells which may be improved as a therapeutic carrier in future. • Coating QDs with polymer seems to be a right choice to be used in medicinal applications both for diagnosis and for therapy

Medical image computing and computer-assisted intervention - MICCAI 2005. Proceedings; Pt. 1

International Nuclear Information System (INIS)

Duncan, J.S.; Gerig, G.

2005-01-01

The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing, structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis. (orig.)

Medical image computing and computer science intervention. MICCAI 2005. Pt. 2. Proceedings

International Nuclear Information System (INIS)

Duncan, J.S.; Yale Univ., New Haven, CT; Gerig, G.

2005-01-01

The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing, structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis. (orig.)

Medical image computing and computer-assisted intervention - MICCAI 2005. Proceedings; Pt. 1

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