In Vivo Real Time Volumetric Synthetic Aperture Ultrasound Imaging

DEFF Research Database (Denmark)

Bouzari, Hamed; Rasmussen, Morten Fischer; Brandt, Andreas Hjelm

2015-01-01

Synthetic aperture (SA) imaging can be used to achieve real-time volumetric ultrasound imaging using 2-D array transducers. The sensitivity of SA imaging is improved by maximizing the acoustic output, but one must consider the limitations of an ultrasound system, both technical and biological....... This paper investigates the in vivo applicability and sensitivity of volumetric SA imaging. Utilizing the transmit events to generate a set of virtual point sources, a frame rate of 25 Hz for a 90° x 90° field-of-view was achieved. Data were obtained using a 3.5 MHz 32 x 32 elements 2-D phased array...... transducer connected to the experimental scanner (SARUS). Proper scaling is applied to the excitation signal such that intensity levels are in compliance with the U.S. Food and Drug Administration regulations for in vivo ultrasound imaging. The measured Mechanical Index and spatial-peak- temporal...

Two-dimensional random arrays for real time volumetric imaging

DEFF Research Database (Denmark)

Davidsen, Richard E.; Jensen, Jørgen Arendt; Smith, Stephen W.

1994-01-01

real time volumetric imaging system, which employs a wide transmit beam and receive mode parallel processing to increase image frame rate. Depth-of-field comparisons were made from simulated on-axis and off-axis beamplots at ranges from 30 to 160 mm for both coaxial and offset transmit and receive......Two-dimensional arrays are necessary for a variety of ultrasonic imaging techniques, including elevation focusing, 2-D phase aberration correction, and real time volumetric imaging. In order to reduce system cost and complexity, sparse 2-D arrays have been considered with element geometries...... selected ad hoc, by algorithm, or by random process. Two random sparse array geometries and a sparse array with a Mills cross receive pattern were simulated and compared to a fully sampled aperture with the same overall dimensions. The sparse arrays were designed to the constraints of the Duke University...

Reducing uncertainties in volumetric image based deformable organ registration

International Nuclear Information System (INIS)

Liang, J.; Yan, D.

2003-01-01

Applying volumetric image feedback in radiotherapy requires image based deformable organ registration. The foundation of this registration is the ability of tracking subvolume displacement in organs of interest. Subvolume displacement can be calculated by applying biomechanics model and the finite element method to human organs manifested on the multiple volumetric images. The calculation accuracy, however, is highly dependent on the determination of the corresponding organ boundary points. Lacking sufficient information for such determination, uncertainties are inevitable--thus diminishing the registration accuracy. In this paper, a method of consuming energy minimization was developed to reduce these uncertainties. Starting from an initial selection of organ boundary point correspondence on volumetric image sets, the subvolume displacement and stress distribution of the whole organ are calculated and the consumed energy due to the subvolume displacements is computed accordingly. The corresponding positions of the initially selected boundary points are then iteratively optimized to minimize the consuming energy under geometry and stress constraints. In this study, a rectal wall delineated from patient CT image was artificially deformed using a computer simulation and utilized to test the optimization. Subvolume displacements calculated based on the optimized boundary point correspondence were compared to the true displacements, and the calculation accuracy was thereby evaluated. Results demonstrate that a significant improvement on the accuracy of the deformable organ registration can be achieved by applying the consuming energy minimization in the organ deformation calculation

Parallel imaging: is GRAPPA a useful acquisition tool for MR imaging intended for volumetric brain analysis?

Directory of Open Access Journals (Sweden)

Frank Anders

2009-08-01

Full Text Available Abstract Background The work presented here investigates parallel imaging applied to T1-weighted high resolution imaging for use in longitudinal volumetric clinical studies involving Alzheimer's disease (AD and Mild Cognitive Impairment (MCI patients. This was in an effort to shorten acquisition times to minimise the risk of motion artefacts caused by patient discomfort and disorientation. The principle question is, "Can parallel imaging be used to acquire images at 1.5 T of sufficient quality to allow volumetric analysis of patient brains?" Methods Optimisation studies were performed on a young healthy volunteer and the selected protocol (including the use of two different parallel imaging acceleration factors was then tested on a cohort of 15 elderly volunteers including MCI and AD patients. In addition to automatic brain segmentation, hippocampus volumes were manually outlined and measured in all patients. The 15 patients were scanned on a second occasion approximately one week later using the same protocol and evaluated in the same manner to test repeatability of measurement using images acquired with the GRAPPA parallel imaging technique applied to the MPRAGE sequence. Results Intraclass correlation tests show that almost perfect agreement between repeated measurements of both segmented brain parenchyma fraction and regional measurement of hippocampi. The protocol is suitable for both global and regional volumetric measurement dementia patients. Conclusion In summary, these results indicate that parallel imaging can be used without detrimental effect to brain tissue segmentation and volumetric measurement and should be considered for both clinical and research studies where longitudinal measurements of brain tissue volumes are of interest.

A feasibility study of digital tomosynthesis for volumetric dental imaging

International Nuclear Information System (INIS)

Cho, M K; Kim, H K; Youn, H; Kim, S S

2012-01-01

We present a volumetric dental tomography method that compensates for insufficient projection views obtained from limited-angle scans. The reconstruction algorithm is based on the backprojection filtering method which employs apodizing filters that reduce out-of-plane blur artifacts and suppress high-frequency noise. In order to accompolish this volumetric imaging two volume-reconstructed datasets are synthesized. These individual datasets provide two different limited-angle scans performed at orthogonal angles. The obtained reconstructed images, using less than 15% of the number of projection views needed for a full skull phantom scan, demonstrate the potential use of the proposed method in dental imaging applications. This method enables a much smaller radiation dose for the patient compared to conventional dental tomography.

Visualization and volumetric structures from MR images of the brain

Energy Technology Data Exchange (ETDEWEB)

Parvin, B.; Johnston, W.; Robertson, D.

1994-03-01

Pinta is a system for segmentation and visualization of anatomical structures obtained from serial sections reconstructed from magnetic resonance imaging. The system approaches the segmentation problem by assigning each volumetric region to an anatomical structure. This is accomplished by satisfying constraints at the pixel level, slice level, and volumetric level. Each slice is represented by an attributed graph, where nodes correspond to regions and links correspond to the relations between regions. These regions are obtained by grouping pixels based on similarity and proximity. The slice level attributed graphs are then coerced to form a volumetric attributed graph, where volumetric consistency can be verified. The main novelty of our approach is in the use of the volumetric graph to ensure consistency from symbolic representations obtained from individual slices. In this fashion, the system allows errors to be made at the slice level, yet removes them when the volumetric consistency cannot be verified. Once the segmentation is complete, the 3D surfaces of the brain can be constructed and visualized.

Volumetric Real-Time Imaging Using a CMUT Ring Array

OpenAIRE

Choe, Jung Woo; Oralkan, Ömer; Nikoozadeh, Amin; Gencel, Mustafa; Stephens, Douglas N.; O’Donnell, Matthew; Sahn, David J.; Khuri-Yakub, Butrus T.

2012-01-01

A ring array provides a very suitable geometry for forward-looking volumetric intracardiac and intravascular ultrasound imaging. We fabricated an annular 64-element capacitive micromachined ultrasonic transducer (CMUT) array featuring a 10-MHz operating frequency and a 1.27-mm outer radius. A custom software suite was developed to run on a PC-based imaging system for real-time imaging using this device.

Real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image for lung cancer radiotherapy.

Science.gov (United States)

Li, Ruijiang; Jia, Xun; Lewis, John H; Gu, Xuejun; Folkerts, Michael; Men, Chunhua; Jiang, Steve B

2010-06-01

To develop an algorithm for real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image for lung cancer radiotherapy. Given a set of volumetric images of a patient at N breathing phases as the training data, deformable image registration was performed between a reference phase and the other N-1 phases, resulting in N-1 deformation vector fields (DVFs). These DVFs can be represented efficiently by a few eigenvectors and coefficients obtained from principal component analysis (PCA). By varying the PCA coefficients, new DVFs can be generated, which, when applied on the reference image, lead to new volumetric images. A volumetric image can then be reconstructed from a single projection image by optimizing the PCA coefficients such that its computed projection matches the measured one. The 3D location of the tumor can be derived by applying the inverted DVF on its position in the reference image. The algorithm was implemented on graphics processing units (GPUs) to achieve real-time efficiency. The training data were generated using a realistic and dynamic mathematical phantom with ten breathing phases. The testing data were 360 cone beam projections corresponding to one gantry rotation, simulated using the same phantom with a 50% increase in breathing amplitude. The average relative image intensity error of the reconstructed volumetric images is 6.9% +/- 2.4%. The average 3D tumor localization error is 0.8 +/- 0.5 mm. On an NVIDIA Tesla C1060 GPU card, the average computation time for reconstructing a volumetric image from each projection is 0.24 s (range: 0.17 and 0.35 s). The authors have shown the feasibility of reconstructing volumetric images and localizing tumor positions in 3D in near real-time from a single x-ray image.

The establishment of the method of three dimension volumetric fusion of emission and transmission images for PET imaging

International Nuclear Information System (INIS)

Zhang Xiangsong; He Zuoxiang

2004-01-01

Objective: To establish the method of three dimension volumetric fusion of emission and transmission images for PET imaging. Methods: The volume data of emission and transmission images acquired with Siemens ECAT HR + PET scanner were transferred to PC computer by local area network. The PET volume data were converted into 8 bit byte type, and scaled to the range of 0-255. The data coordinates of emission and transmission images were normalized by three-dimensional coordinate conversion in the same way. The images were fused with the mode of alpha-blending. The accuracy of image fusion was confirmed by its clinical application in 13 cases. Results: The three dimension volumetric fusion of emission and transmission images clearly displayed the silhouette and anatomic configuration in chest, including chest wall, lung, heart, mediastinum, et al. Forty-eight lesions in chest in 13 cases were accurately located by the image fusion. Conclusions: The volume data of emission and transmission images acquired with Siemens ECAT HR + PET scanner have the same data coordinate. The three dimension fusion software can conveniently used for the three dimension volumetric fusion of emission and transmission images, and also can correctly locate the lesions in chest

SemVisM: semantic visualizer for medical image

Science.gov (United States)

Landaeta, Luis; La Cruz, Alexandra; Baranya, Alexander; Vidal, María.-Esther

2015-01-01

SemVisM is a toolbox that combines medical informatics and computer graphics tools for reducing the semantic gap between low-level features and high-level semantic concepts/terms in the images. This paper presents a novel strategy for visualizing medical data annotated semantically, combining rendering techniques, and segmentation algorithms. SemVisM comprises two main components: i) AMORE (A Modest vOlume REgister) to handle input data (RAW, DAT or DICOM) and to initially annotate the images using terms defined on medical ontologies (e.g., MesH, FMA or RadLex), and ii) VOLPROB (VOlume PRObability Builder) for generating the annotated volumetric data containing the classified voxels that belong to a particular tissue. SemVisM is built on top of the semantic visualizer ANISE.1

X-ray volumetric imaging in image-guided radiotherapy: The new standard in on-treatment imaging

International Nuclear Information System (INIS)

McBain, Catherine A.; Henry, Ann M.; Sykes, Jonathan; Amer, Ali; Marchant, Tom; Moore, Christopher M.; Davies, Julie; Stratford, Julia; McCarthy, Claire; Porritt, Bridget; Williams, Peter; Khoo, Vincent S.; Price, Pat

2006-01-01

Purpose: X-ray volumetric imaging (XVI) for the first time allows for the on-treatment acquisition of three-dimensional (3D) kV cone beam computed tomography (CT) images. Clinical imaging using the Synergy System (Elekta, Crawley, UK) commenced in July 2003. This study evaluated image quality and dose delivered and assessed clinical utility for treatment verification at a range of anatomic sites. Methods and Materials: Single XVIs were acquired from 30 patients undergoing radiotherapy for tumors at 10 different anatomic sites. Patients were imaged in their setup position. Radiation doses received were measured using TLDs on the skin surface. The utility of XVI in verifying target volume coverage was qualitatively assessed by experienced clinicians. Results: X-ray volumetric imaging acquisition was completed in the treatment position at all anatomic sites. At sites where a full gantry rotation was not possible, XVIs were reconstructed from projection images acquired from partial rotations. Soft-tissue definition of organ boundaries allowed direct assessment of 3D target volume coverage at all sites. Individual image quality depended on both imaging parameters and patient characteristics. Radiation dose ranged from 0.003 Gy in the head to 0.03 Gy in the pelvis. Conclusions: On-treatment XVI provided 3D verification images with soft-tissue definition at all anatomic sites at acceptably low radiation doses. This technology sets a new standard in treatment verification and will facilitate novel adaptive radiotherapy techniques

Systematic Parameterization, Storage, and Representation of Volumetric DICOM Data

OpenAIRE

Fischer, Felix; Selver, M. Alper; Gezer, Sinem; Dicle, O?uz; Hillen, Walter

2015-01-01

Tomographic medical imaging systems produce hundreds to thousands of slices, enabling three-dimensional (3D) analysis. Radiologists process these images through various tools and techniques in order to generate 3D renderings for various applications, such as surgical planning, medical education, and volumetric measurements. To save and store these visualizations, current systems use snapshots or video exporting, which prevents further optimizations and requires the storage of significant addi...

A spiral-based volumetric acquisition for MR temperature imaging.

Science.gov (United States)

Fielden, Samuel W; Feng, Xue; Zhao, Li; Miller, G Wilson; Geeslin, Matthew; Dallapiazza, Robert F; Elias, W Jeffrey; Wintermark, Max; Butts Pauly, Kim; Meyer, Craig H

2018-06-01

To develop a rapid pulse sequence for volumetric MR thermometry. Simulations were carried out to assess temperature deviation, focal spot distortion/blurring, and focal spot shift across a range of readout durations and maximum temperatures for Cartesian, spiral-out, and retraced spiral-in/out (RIO) trajectories. The RIO trajectory was applied for stack-of-spirals 3D imaging on a real-time imaging platform and preliminary evaluation was carried out compared to a standard 2D sequence in vivo using a swine brain model, comparing maximum and mean temperatures measured between the two methods, as well as the temporal standard deviation measured by the two methods. In simulations, low-bandwidth Cartesian trajectories showed substantial shift of the focal spot, whereas both spiral trajectories showed no shift while maintaining focal spot geometry. In vivo, the 3D sequence achieved real-time 4D monitoring of thermometry, with an update time of 2.9-3.3 s. Spiral imaging, and RIO imaging in particular, is an effective way to speed up volumetric MR thermometry. Magn Reson Med 79:3122-3127, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

Energy Technology Data Exchange (ETDEWEB)

Mishra, Pankaj, E-mail: pankaj.mishra@varian.com; Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H. [Brigham and Women' s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Li, Ruijiang [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305 (United States)

2014-08-15

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model

Rapidly-steered single-element ultrasound for real-time volumetric imaging and guidance

Science.gov (United States)

Stauber, Mark; Western, Craig; Solek, Roman; Salisbury, Kenneth; Hristov, Dmitre; Schlosser, Jeffrey

2016-03-01

Volumetric ultrasound (US) imaging has the potential to provide real-time anatomical imaging with high soft-tissue contrast in a variety of diagnostic and therapeutic guidance applications. However, existing volumetric US machines utilize "wobbling" linear phased array or matrix phased array transducers which are costly to manufacture and necessitate bulky external processing units. To drastically reduce cost, improve portability, and reduce footprint, we propose a rapidly-steered single-element volumetric US imaging system. In this paper we explore the feasibility of this system with a proof-of-concept single-element volumetric US imaging device. The device uses a multi-directional raster-scan technique to generate a series of two-dimensional (2D) slices that were reconstructed into three-dimensional (3D) volumes. At 15 cm depth, 90° lateral field of view (FOV), and 20° elevation FOV, the device produced 20-slice volumes at a rate of 0.8 Hz. Imaging performance was evaluated using an US phantom. Spatial resolution was 2.0 mm, 4.7 mm, and 5.0 mm in the axial, lateral, and elevational directions at 7.5 cm. Relative motion of phantom targets were automatically tracked within US volumes with a mean error of -0.3+/-0.3 mm, -0.3+/-0.3 mm, and -0.1+/-0.5 mm in the axial, lateral, and elevational directions, respectively. The device exhibited a mean spatial distortion error of 0.3+/-0.9 mm, 0.4+/-0.7 mm, and -0.3+/-1.9 in the axial, lateral, and elevational directions. With a production cost near $1000, the performance characteristics of the proposed system make it an ideal candidate for diagnostic and image-guided therapy applications where form factor and low cost are paramount.

WE-D-BRB-03: Current State of Volumetric Image Guidance for Proton Therapy

Energy Technology Data Exchange (ETDEWEB)

Hua, C. [St. Jude Children’s Research Hospital (United States)

2016-06-15

The goal of this session is to review the physics of proton therapy, treatment planning techniques, and the use of volumetric imaging in proton therapy. The course material covers the physics of proton interaction with matter and physical characteristics of clinical proton beams. It will provide information on proton delivery systems and beam delivery techniques for double scattering (DS), uniform scanning (US), and pencil beam scanning (PBS). The session covers the treatment planning strategies used in DS, US, and PBS for various anatomical sites, methods to address uncertainties in proton therapy and uncertainty mitigation to generate robust treatment plans. It introduces the audience to the current status of image guided proton therapy and clinical applications of CBCT for proton therapy. It outlines the importance of volumetric imaging in proton therapy. Learning Objectives: Gain knowledge in proton therapy physics, and treatment planning for proton therapy including intensity modulated proton therapy. The current state of volumetric image guidance equipment in proton therapy. Clinical applications of CBCT and its advantage over orthogonal imaging for proton therapy. B. Teo, B.K Teo had received travel funds from IBA in 2015.

WE-D-BRB-03: Current State of Volumetric Image Guidance for Proton Therapy

International Nuclear Information System (INIS)

Hua, C.

2016-01-01

The goal of this session is to review the physics of proton therapy, treatment planning techniques, and the use of volumetric imaging in proton therapy. The course material covers the physics of proton interaction with matter and physical characteristics of clinical proton beams. It will provide information on proton delivery systems and beam delivery techniques for double scattering (DS), uniform scanning (US), and pencil beam scanning (PBS). The session covers the treatment planning strategies used in DS, US, and PBS for various anatomical sites, methods to address uncertainties in proton therapy and uncertainty mitigation to generate robust treatment plans. It introduces the audience to the current status of image guided proton therapy and clinical applications of CBCT for proton therapy. It outlines the importance of volumetric imaging in proton therapy. Learning Objectives: Gain knowledge in proton therapy physics, and treatment planning for proton therapy including intensity modulated proton therapy. The current state of volumetric image guidance equipment in proton therapy. Clinical applications of CBCT and its advantage over orthogonal imaging for proton therapy. B. Teo, B.K Teo had received travel funds from IBA in 2015.

From medical imaging data to 3D printed anatomical models.

Directory of Open Access Journals (Sweden)

Thore M Bücking

Full Text Available Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.

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.

A feasibility study for image guided radiotherapy using low dose, high speed, cone beam X-ray volumetric imaging

International Nuclear Information System (INIS)

Sykes, Jonathan R.; Amer, Ali; Czajka, Jadwiga; Moore, Christopher J.

2005-01-01

Background and purpose: Image Guidance of patient set-up for radiotherapy can be achieved by acquiring X-ray volumetric images (XVI) with Elekta Synergy and registering these to the planning CT scan. This enables full 3D registration of structures from similar 3D imaging modalities and offers superior image quality, rotational set-up information and a large field of view. This study uses the head section of the Rando phantom to demonstrate a new paradigm of faster, lower dose XVI that still allows registration to high precision. Materials and methods: One high exposure XVI scan and one low exposure XVI scan were performed with a Rando Head Phantom. The second scan was used to simulate ultra low dose, fast acquisition, full and half scans by discarding a large number of projections before reconstruction. Dose measurements were performed using Thermo Luminescent Dosimeters (TLD) and an ion chamber. The reconstructed XVI scans were automatically registered with a helical CT scan of the Rando Head using the volumetric, grey-level, cross-correlation algorithm implemented in the Syntegra software package (Philips Medical Systems). Reproducibility of the registration process was investigated. Results: In both XVI scans the body surface, bone-tissue and tissue air interfaces were clearly visible. Although the subjective image quality of the low dose cone beam scan was reduced, registration of both cone beam scans with the planning CT scan agreed within 0.1 mm and 0.1 deg. Dose to the patient was reduced from 28 mGy to less than 1 mGy and the equivalent scan speed reduced to one minute or less. Conclusions: Automatic 3D registration of high speed, ultra low dose XVI scans with the planning CT scan can be used for precision 3D patient set-up verification/image guidance on a daily basis with out loss of accuracy when compared to higher dose XVI scans

WE-G-BRF-04: Robust Real-Time Volumetric Imaging Based On One Single Projection

International Nuclear Information System (INIS)

Xu, Y; Yan, H; Ouyang, L; Wang, J; Jiang, S; Jia, X; Zhou, L

2014-01-01

Purpose: Real-time volumetric imaging is highly desirable to provide instantaneous image guidance for lung radiation therapy. This study proposes a scheme to achieve this goal using one single projection by utilizing sparse learning and a principal component analysis (PCA) based lung motion model. Methods: A patient-specific PCA-based lung motion model is first constructed by analyzing deformable vector fields (DVFs) between a reference image and 4DCT images at each phase. At the training stage, we “learn” the relationship between the DVFs and the projection using sparse learning. Specifically, we first partition the projections into patches, and then apply sparse learning to automatically identify patches that best correlate with the principal components of the DVFs. Once the relationship is established, at the application stage, we first employ a patchbased intensity correction method to overcome the problem of different intensity scale between the calculated projection in the training stage and the measured projection in the application stage. The corrected projection image is then fed to the trained model to derive a DVF, which is applied to the reference image, yielding a volumetric image corresponding to the projection. We have validated our method through a NCAT phantom simulation case and one experiment case. Results: Sparse learning can automatically select those patches containing motion information, such as those around diaphragm. For the simulation case, over 98% of the lung region pass the generalized gamma test (10HU/1mm), indicating combined accuracy in both intensity and spatial domain. For the experimental case, the average tumor localization errors projected to the imager are 0.68 mm and 0.4 mm on the axial and tangential direction, respectively. Conclusion: The proposed method is capable of accurately generating a volumetric image using one single projection. It will potentially offer real-time volumetric image guidance to facilitate lung

WE-G-BRF-04: Robust Real-Time Volumetric Imaging Based On One Single Projection

Energy Technology Data Exchange (ETDEWEB)

Xu, Y [UT Southwestern Medical Center, Dallas, TX (United States); Southern Medical University, Guangzhou (China); Yan, H; Ouyang, L; Wang, J; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States); Zhou, L [Southern Medical University, Guangzhou (China)

2014-06-15

Purpose: Real-time volumetric imaging is highly desirable to provide instantaneous image guidance for lung radiation therapy. This study proposes a scheme to achieve this goal using one single projection by utilizing sparse learning and a principal component analysis (PCA) based lung motion model. Methods: A patient-specific PCA-based lung motion model is first constructed by analyzing deformable vector fields (DVFs) between a reference image and 4DCT images at each phase. At the training stage, we “learn” the relationship between the DVFs and the projection using sparse learning. Specifically, we first partition the projections into patches, and then apply sparse learning to automatically identify patches that best correlate with the principal components of the DVFs. Once the relationship is established, at the application stage, we first employ a patchbased intensity correction method to overcome the problem of different intensity scale between the calculated projection in the training stage and the measured projection in the application stage. The corrected projection image is then fed to the trained model to derive a DVF, which is applied to the reference image, yielding a volumetric image corresponding to the projection. We have validated our method through a NCAT phantom simulation case and one experiment case. Results: Sparse learning can automatically select those patches containing motion information, such as those around diaphragm. For the simulation case, over 98% of the lung region pass the generalized gamma test (10HU/1mm), indicating combined accuracy in both intensity and spatial domain. For the experimental case, the average tumor localization errors projected to the imager are 0.68 mm and 0.4 mm on the axial and tangential direction, respectively. Conclusion: The proposed method is capable of accurately generating a volumetric image using one single projection. It will potentially offer real-time volumetric image guidance to facilitate lung

System analysis of formation and perception processes of three-dimensional images in volumetric displays

Science.gov (United States)

Bolshakov, Alexander; Sgibnev, Arthur

2018-03-01

One of the promising devices is currently a volumetric display. Volumetric displays capable to visualize complex three-dimensional information as nearly as possible to its natural – volume form without the use of special glasses. The invention and implementation of volumetric display technology will expand opportunities of information visualization in various spheres of human activity. The article attempts to structure and describe the interrelation of the essential characteristics of objects in the area of volumetric visualization. Also there is proposed a method of calculation of estimate total number of voxels perceived by observers during the 3D demonstration, generated using a volumetric display with a rotating screen. In the future, it is planned to expand the described technique and implement a system for estimation the quality of generated images, depending on the types of biplanes and their initial characteristics.

AMIDE: A Free Software Tool for Multimodality Medical Image Analysis

Directory of Open Access Journals (Sweden)

Andreas Markus Loening

2003-07-01

Full Text Available Amide's a Medical Image Data Examiner (AMIDE has been developed as a user-friendly, open-source software tool for displaying and analyzing multimodality volumetric medical images. Central to the package's abilities to simultaneously display multiple data sets (e.g., PET, CT, MRI and regions of interest is the on-demand data reslicing implemented within the program. Data sets can be freely shifted, rotated, viewed, and analyzed with the program automatically handling interpolation as needed from the original data. Validation has been performed by comparing the output of AMIDE with that of several existing software packages. AMIDE runs on UNIX, Macintosh OS X, and Microsoft Windows platforms, and it is freely available with source code under the terms of the GNU General Public License.

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)

X-ray detectors in medical imaging

International Nuclear Information System (INIS)

Spahn, Martin

2013-01-01

Healthcare systems are subject to continuous adaptation, following trends such as the change of demographic structures, the rise of life-style related and chronic diseases, and the need for efficient and outcome-oriented procedures. This also influences the design of new imaging systems as well as their components. The applications of X-ray imaging in the medical field are manifold and have led to dedicated modalities supporting specific imaging requirements, for example in computed tomography (CT), radiography, angiography, surgery or mammography, delivering projection or volumetric imaging data. Depending on the clinical needs, some X-ray systems enable diagnostic imaging while others support interventional procedures. X-ray detector design requirements for the different medical applications can vary strongly with respect to size and shape, spatial resolution, frame rates and X-ray flux, among others. Today, integrating X-ray detectors are in common use. They are predominantly based on scintillators (e.g. CsI or Gd 2 O 2 S) and arrays of photodiodes made from crystalline silicon (Si) or amorphous silicon (a-Si) or they employ semiconductors (e.g. Se) with active a-Si readout matrices. Ongoing and future developments of X-ray detectors will include optimization of current state-of-the-art integrating detectors in terms of performance and cost, will enable the usage of large size CMOS-based detectors, and may facilitate photon counting techniques with the potential to further enhance performance characteristics and foster the prospect of new clinical applications

WE-D-303-02: Applications of Volumetric Images Generated with a Respiratory Motion Model Based On An External Surrogate Signal

International Nuclear Information System (INIS)

Hurwitz, M; Williams, C; Dhou, S; Lewis, J; Mishra, P

2015-01-01

Purpose: Respiratory motion can vary significantly over the course of simulation and treatment. Our goal is to use volumetric images generated with a respiratory motion model to improve the definition of the internal target volume (ITV) and the estimate of delivered dose. Methods: Ten irregular patient breathing patterns spanning 35 seconds each were incorporated into a digital phantom. Ten images over the first five seconds of breathing were used to emulate a 4DCT scan, build the ITV, and generate a patient-specific respiratory motion model which correlated the measured trajectories of markers placed on the patients’ chests with the motion of the internal anatomy. This model was used to generate volumetric images over the subsequent thirty seconds of breathing. The increase in the ITV taking into account the full 35 seconds of breathing was assessed with ground-truth and model-generated images. For one patient, a treatment plan based on the initial ITV was created and the delivered dose was estimated using images from the first five seconds as well as ground-truth and model-generated images from the next 30 seconds. Results: The increase in the ITV ranged from 0.2 cc to 6.9 cc for the ten patients based on ground-truth information. The model predicted this increase in the ITV with an average error of 0.8 cc. The delivered dose to the tumor (D95) changed significantly from 57 Gy to 41 Gy when estimated using 5 seconds and 30 seconds, respectively. The model captured this effect, giving an estimated D95 of 44 Gy. Conclusion: A respiratory motion model generating volumetric images of the internal patient anatomy could be useful in estimating the increase in the ITV due to irregular breathing during simulation and in assessing delivered dose during treatment. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc. and Radiological Society of North America Research Scholar Grant #RSCH1206

Time-resolved computed tomography of the liver: retrospective, multi-phase image reconstruction derived from volumetric perfusion imaging

Energy Technology Data Exchange (ETDEWEB)

Fischer, Michael A.; Kartalis, Nikolaos; Aspelin, Peter; Albiin, Nils; Brismar, Torkel B. [Karolinska University Hospital, Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm (Sweden); Leidner, Bertil; Svensson, Anders [Karolinska University Hospital, Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm (Sweden); Karolinska University Hospital Huddinge, Department of Radiology, Stockholm (Sweden)

2014-01-15

To assess feasibility and image quality (IQ) of a new post-processing algorithm for retrospective extraction of an optimised multi-phase CT (time-resolved CT) of the liver from volumetric perfusion imaging. Sixteen patients underwent clinically indicated perfusion CT using 4D spiral mode of dual-source 128-slice CT. Three image sets were reconstructed: motion-corrected and noise-reduced (MCNR) images derived from 4D raw data; maximum and average intensity projections (time MIP/AVG) of the arterial/portal/portal-venous phases and all phases (total MIP/ AVG) derived from retrospective fusion of dedicated MCNR split series. Two readers assessed the IQ, detection rate and evaluation time; one reader assessed image noise and lesion-to-liver contrast. Time-resolved CT was feasible in all patients. Each post-processing step yielded a significant reduction of image noise and evaluation time, maintaining lesion-to-liver contrast. Time MIPs/AVGs showed the highest overall IQ without relevant motion artefacts and best depiction of arterial and portal/portal-venous phases respectively. Time MIPs demonstrated a significantly higher detection rate for arterialised liver lesions than total MIPs/AVGs and the raw data series. Time-resolved CT allows data from volumetric perfusion imaging to be condensed into an optimised multi-phase liver CT, yielding a superior IQ and higher detection rate for arterialised liver lesions than the raw data series. (orig.)

Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma

International Nuclear Information System (INIS)

Grossmann, Patrick; Gutman, David A.; Dunn, William D. Jr; Holder, Chad A.; Aerts, Hugo J. W. L.

2016-01-01

Glioblastoma (GBM) tumors exhibit strong phenotypic differences that can be quantified using magnetic resonance imaging (MRI), but the underlying biological drivers of these imaging phenotypes remain largely unknown. An Imaging-Genomics analysis was performed to reveal the mechanistic associations between MRI derived quantitative volumetric tumor phenotype features and molecular pathways. One hundred fourty one patients with presurgery MRI and survival data were included in our analysis. Volumetric features were defined, including the necrotic core (NE), contrast-enhancement (CE), abnormal tumor volume assessed by post-contrast T1w (tumor bulk or TB), tumor-associated edema based on T2-FLAIR (ED), and total tumor volume (TV), as well as ratios of these tumor components. Based on gene expression where available (n = 91), pathway associations were assessed using a preranked gene set enrichment analysis. These results were put into context of molecular subtypes in GBM and prognostication. Volumetric features were significantly associated with diverse sets of biological processes (FDR < 0.05). While NE and TB were enriched for immune response pathways and apoptosis, CE was associated with signal transduction and protein folding processes. ED was mainly enriched for homeostasis and cell cycling pathways. ED was also the strongest predictor of molecular GBM subtypes (AUC = 0.61). CE was the strongest predictor of overall survival (C-index = 0.6; Noether test, p = 4x10 −4 ). GBM volumetric features extracted from MRI are significantly enriched for information about the biological state of a tumor that impacts patient outcomes. Clinical decision-support systems could exploit this information to develop personalized treatment strategies on the basis of noninvasive imaging. The online version of this article (doi:10.1186/s12885-016-2659-5) contains supplementary material, which is available to authorized users

A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering.

Science.gov (United States)

Banerjee, Pat; Hu, Mengqi; Kannan, Rahul; Krishnaswamy, Srinivasan

2017-08-01

The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as magnetic resonance imaging (MRI) or computed tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating 3D models by automating the segmentation of CT images based on the pixel contrast for integrating the interface between Sensimmer and medical imaging devices, using the volumetric approach, Hough transform method, and manual centering method. Hence, automating the process has reduced the segmentation time by 56.35% while maintaining the same accuracy of the output at ±2 voxels.

Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images

Science.gov (United States)

Suzani, Amin; Rasoulian, Abtin; Seitel, Alexander; Fels, Sidney; Rohling, Robert N.; Abolmaesumi, Purang

2015-03-01

This paper proposes an automatic method for vertebra localization, labeling, and segmentation in multi-slice Magnetic Resonance (MR) images. Prior work in this area on MR images mostly requires user interaction while our method is fully automatic. Cubic intensity-based features are extracted from image voxels. A deep learning approach is used for simultaneous localization and identification of vertebrae. The localized points are refined by local thresholding in the region of the detected vertebral column. Thereafter, a statistical multi-vertebrae model is initialized on the localized vertebrae. An iterative Expectation Maximization technique is used to register the vertebral body of the model to the image edges and obtain a segmentation of the lumbar vertebral bodies. The method is evaluated by applying to nine volumetric MR images of the spine. The results demonstrate 100% vertebra identification and a mean surface error of below 2.8 mm for 3D segmentation. Computation time is less than three minutes per high-resolution volumetric image.

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

Science.gov (United States)

Kontos, Despina; Xing, Ye; Bakic, Predrag R.; Conant, Emily F.; Maidment, Andrew D. A.

2010-03-01

We performed a study to compare methods for volumetric breast density estimation in digital mammography (DM) and magnetic resonance imaging (MRI) for a high-risk population of women. DM and MRI images of the unaffected breast from 32 women with recently detected abnormalities and/or previously diagnosed breast cancer (age range 31-78 yrs, mean 50.3 yrs) were retrospectively analyzed. DM images were analyzed using QuantraTM (Hologic Inc). The MRI images were analyzed using a fuzzy-C-means segmentation algorithm on the T1 map. Both methods were compared to Cumulus (Univ. Toronto). Volumetric breast density estimates from DM and MRI are highly correlated (r=0.90, pwomen with very low-density breasts (peffects in MRI and differences in the computational aspects of the image analysis methods in MRI and DM. The good correlation between the volumetric and the area-based measures, shown to correlate with breast cancer risk, suggests that both DM and MRI volumetric breast density measures can aid in breast cancer risk assessment. Further work is underway to fully-investigate the association between volumetric breast density measures and breast cancer risk.

Quantitative volumetric Raman imaging of three dimensional cell cultures

KAUST Repository

Kallepitis, Charalambos

2017-03-22

The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell–material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.

Quantitative volumetric Raman imaging of three dimensional cell cultures

Science.gov (United States)

Kallepitis, Charalambos; Bergholt, Mads S.; Mazo, Manuel M.; Leonardo, Vincent; Skaalure, Stacey C.; Maynard, Stephanie A.; Stevens, Molly M.

2017-03-01

The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell-material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.

SU-F-J-54: Towards Real-Time Volumetric Imaging Using the Treatment Beam and KV Beam

Energy Technology Data Exchange (ETDEWEB)

Chen, M; Rozario, T; Liu, A; Jiang, S; Lu, W [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: Existing real-time imaging uses dual (orthogonal) kV beam fluoroscopies and may result in significant amount of extra radiation to patients, especially for prolonged treatment cases. In addition, kV projections only provide 2D information, which is insufficient for in vivo dose reconstruction. We propose real-time volumetric imaging using prior knowledge of pre-treatment 4D images and real-time 2D transit data of treatment beam and kV beam. Methods: The pre-treatment multi-snapshot volumetric images are used to simulate 2D projections of both the treatment beam and kV beam, respectively, for each treatment field defined by the control point. During radiation delivery, the transit signals acquired by the electronic portal image device (EPID) are processed for every projection and compared with pre-calculation by cross-correlation for phase matching and thus 3D snapshot identification or real-time volumetric imaging. The data processing involves taking logarithmic ratios of EPID signals with respect to the air scan to reduce modeling uncertainties in head scatter fluence and EPID response. Simulated 2D projections are also used to pre-calculate confidence levels in phase matching. Treatment beam projections that have a low confidence level either in pre-calculation or real-time acquisition will trigger kV beams so that complementary information can be exploited. In case both the treatment beam and kV beam return low confidence in phase matching, a predicted phase based on linear regression will be generated. Results: Simulation studies indicated treatment beams provide sufficient confidence in phase matching for most cases. At times of low confidence from treatment beams, kV imaging provides sufficient confidence in phase matching due to its complementary configuration. Conclusion: The proposed real-time volumetric imaging utilizes the treatment beam and triggers kV beams for complementary information when the treatment beam along does not provide sufficient

The approximate entropy concept extended to three dimensions for calibrated, single parameter structural complexity interrogation of volumetric images.

Science.gov (United States)

Moore, Christopher; Marchant, Thomas

2017-07-12

Reconstructive volumetric imaging permeates medical practice because of its apparently clear depiction of anatomy. However, the tell tale signs of abnormality and its delineation for treatment demand experts work at the threshold of visibility for hints of structure. Hitherto, a suitable assistive metric that chimes with clinical experience has been absent. This paper develops the complexity measure approximate entropy (ApEn) from its 1D physiological origin into a three-dimensional (3D) algorithm to fill this gap. The first 3D algorithm for this is presented in detail. Validation results for known test arrays are followed by a comparison of fan-beam and cone-beam x-ray computed tomography image volumes used in image guided radiotherapy for cancer. Results show the structural detail down to individual voxel level, the strength of which is calibrated by the ApEn process itself. The potential for application in machine assisted manual interaction and automated image processing and interrogation, including radiomics associated with predictive outcome modeling, is discussed.

The approximate entropy concept extended to three dimensions for calibrated, single parameter structural complexity interrogation of volumetric images

Science.gov (United States)

Moore, Christopher; Marchant, Thomas

2017-08-01

Reconstructive volumetric imaging permeates medical practice because of its apparently clear depiction of anatomy. However, the tell tale signs of abnormality and its delineation for treatment demand experts work at the threshold of visibility for hints of structure. Hitherto, a suitable assistive metric that chimes with clinical experience has been absent. This paper develops the complexity measure approximate entropy (ApEn) from its 1D physiological origin into a three-dimensional (3D) algorithm to fill this gap. The first 3D algorithm for this is presented in detail. Validation results for known test arrays are followed by a comparison of fan-beam and cone-beam x-ray computed tomography image volumes used in image guided radiotherapy for cancer. Results show the structural detail down to individual voxel level, the strength of which is calibrated by the ApEn process itself. The potential for application in machine assisted manual interaction and automated image processing and interrogation, including radiomics associated with predictive outcome modeling, is discussed.

Volumetric real-time imaging using a CMUT ring array.

Science.gov (United States)

Choe, Jung Woo; Oralkan, Ömer; Nikoozadeh, Amin; Gencel, Mustafa; Stephens, Douglas N; O'Donnell, Matthew; Sahn, David J; Khuri-Yakub, Butrus T

2012-06-01

A ring array provides a very suitable geometry for forward-looking volumetric intracardiac and intravascular ultrasound imaging. We fabricated an annular 64-element capacitive micromachined ultrasonic transducer (CMUT) array featuring a 10-MHz operating frequency and a 1.27-mm outer radius. A custom software suite was developed to run on a PC-based imaging system for real-time imaging using this device. This paper presents simulated and experimental imaging results for the described CMUT ring array. Three different imaging methods--flash, classic phased array (CPA), and synthetic phased array (SPA)--were used in the study. For SPA imaging, two techniques to improve the image quality--Hadamard coding and aperture weighting--were also applied. The results show that SPA with Hadamard coding and aperture weighting is a good option for ring-array imaging. Compared with CPA, it achieves better image resolution and comparable signal-to-noise ratio at a much faster image acquisition rate. Using this method, a fast frame rate of up to 463 volumes per second is achievable if limited only by the ultrasound time of flight; with the described system we reconstructed three cross-sectional images in real-time at 10 frames per second, which was limited by the computation time in synthetic beamforming.

Semiautomated volumetric response evaluation as an imaging biomarker in superior sulcus tumors

International Nuclear Information System (INIS)

Vos, C.G.; Paul, M.A.; Dahele, M.; Soernsen de Koste, J.R. van; Senan, S.; Bahce, I.; Smit, E.F.; Thunnissen, E.; Hartemink, K.J.

2014-01-01

Volumetric response to therapy has been suggested as a biomarker for patient-centered outcomes. The primary aim of this pilot study was to investigate whether the volumetric response to induction chemoradiotherapy was associated with pathological complete response (pCR) or survival in patients with superior sulcus tumors managed with trimodality therapy. The secondary aim was to evaluate a semiautomated method for serial volume assessment. In this retrospective study, treatment outcomes were obtained from a departmental database. The tumor was delineated on the computed tomography (CT) scan used for radiotherapy planning, which was typically performed during the first cycle of chemotherapy. These contours were transferred to the post-chemoradiotherapy diagnostic CT scan using deformable image registration (DIR) with/without manual editing. CT scans from 30 eligible patients were analyzed. Median follow-up was 51 months. Neither absolute nor relative reduction in tumor volume following chemoradiotherapy correlated with pCR or 2-year survival. The tumor volumes determined by DIR alone and DIR + manual editing correlated to a high degree (R 2 = 0.99, P < 0.01). Volumetric response to induction chemoradiotherapy was not correlated with pCR or survival in patients with superior sulcus tumors managed with trimodality therapy. DIR-based contour propagation merits further evaluation as a tool for serial volumetric assessment. (orig.)

Dedicated mobile volumetric cone-beam computed tomography for human brain imaging: A phantom study.

Science.gov (United States)

Ryu, Jong-Hyun; Kim, Tae-Hoon; Jeong, Chang-Won; Jun, Hong-Young; Heo, Dong-Woon; Lee, Jinseok; Kim, Kyong-Woo; Yoon, Kwon-Ha

2015-01-01

Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased (p < 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 μ m at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Volumetric fat-water separated T2-weighted MRI

International Nuclear Information System (INIS)

Vasanawala, Shreyas S.; Sonik, Arvind; Madhuranthakam, Ananth J.; Venkatesan, Ramesh; Lai, Peng; Brau, Anja C.S.

2011-01-01

Pediatric body MRI exams often cover multiple body parts, making the development of broadly applicable protocols and obtaining uniform fat suppression a challenge. Volumetric T2 imaging with Dixon-type fat-water separation might address this challenge, but it is a lengthy process. We develop and evaluate a faster two-echo approach to volumetric T2 imaging with fat-water separation. A volumetric spin-echo sequence was modified to include a second shifted echo so two image sets are acquired. A region-growing reconstruction approach was developed to decompose separate water and fat images. Twenty-six children were recruited with IRB approval and informed consent. Fat-suppression quality was graded by two pediatric radiologists and compared against conventional fat-suppressed fast spin-echo T2-W images. Additionally, the value of in- and opposed-phase images was evaluated. Fat suppression on volumetric images had high quality in 96% of cases (95% confidence interval of 80-100%) and were preferred over or considered equivalent to conventional two-dimensional fat-suppressed FSE T2 imaging in 96% of cases (95% confidence interval of 78-100%). In- and opposed-phase images had definite value in 12% of cases. Volumetric fat-water separated T2-weighted MRI is feasible and is likely to yield improved fat suppression over conventional fat-suppressed T2-weighted imaging. (orig.)

Volumetric BOLD fMRI simulation: from neurovascular coupling to multivoxel imaging

International Nuclear Information System (INIS)

Chen, Zikuan; Calhoun, Vince

2012-01-01

The blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) modality has been numerically simulated by calculating single voxel signals. However, the observation on single voxel signals cannot provide information regarding the spatial distribution of the signals. Specifically, a single BOLD voxel signal simulation cannot answer the fundamental question: is the magnetic resonance (MR) image a replica of its underling magnetic susceptibility source? In this paper, we address this problem by proposing a multivoxel volumetric BOLD fMRI simulation model and a susceptibility expression formula for linear neurovascular coupling process, that allow us to examine the BOLD fMRI procedure from neurovascular coupling to MR image formation. Since MRI technology only senses the magnetism property, we represent a linear neurovascular-coupled BOLD state by a magnetic susceptibility expression formula, which accounts for the parameters of cortical vasculature, intravascular blood oxygenation level, and local neuroactivity. Upon the susceptibility expression of a BOLD state, we carry out volumetric BOLD fMRI simulation by calculating the fieldmap (established by susceptibility magnetization) and the complex multivoxel MR image (by intravoxel dephasing). Given the predefined susceptibility source and the calculated complex MR image, we compare the MR magnitude (phase, respectively) image with the predefined susceptibility source (the calculated fieldmap) by spatial correlation. The spatial correlation between the MR magnitude image and the magnetic susceptibility source is about 0.90 for the settings of T E = 30 ms, B 0 = 3 T, voxel size = 100 micron, vessel radius = 3 micron, and blood volume fraction = 2%. Using these parameters value, the spatial correlation between the MR phase image and the susceptibility-induced fieldmap is close to 1.00. Our simulation results show that the MR magnitude image is not an exact replica of the magnetic susceptibility

Radiology resident MR and CT image analysis skill assessment using an interactive volumetric simulation tool - the RadioLOG project

International Nuclear Information System (INIS)

Gondim Teixeira, Pedro Augusto; Leplat, Christophe; Cendre, Romain; Hossu, Gabriela; Felblinger, Jacques; Blum, Alain; Braun, Marc

2017-01-01

Assess the use of a volumetric simulation tool for the evaluation of radiology resident MR and CT interpretation skills. Forty-three participants were evaluated with a software allowing the visualisation of multiple volumetric image series. There were 7 medical students, 28 residents and 8 senior radiologists among the participants. Residents were divided into two sub-groups (novice and advanced). The test was composed of 15 exercises on general radiology and lasted 45 min. Participants answered a questionnaire on their experience with the test using a 5-point Likert scale. This study was approved by the dean of the medical school and did not require ethics committee approval. The reliability of the test was good with a Cronbach alpha value of 0.9. Test scores were significantly different in all sub-groups studies (p < 0.0225). The relation between test scores and the year of residency was logarithmic (R"2 = 0.974). Participants agreed that the test reflected their radiological practice (3.9 ± 0.9 on a 5-point scale) and was better than the conventional evaluation methods (4.6 ± 0.5 on a 5-point scale). This software provides a high quality evaluation tool for the assessment of the interpretation skills in radiology residents. (orig.)

Radiology resident MR and CT image analysis skill assessment using an interactive volumetric simulation tool - the RadioLOG project

Energy Technology Data Exchange (ETDEWEB)

Gondim Teixeira, Pedro Augusto; Leplat, Christophe [CHRU-Nancy Hopital Central, Service d' Imagerie Guilloz, Nancy (France); Universite de Lorraine, IADI U947, Nancy (France); Cendre, Romain [INSERM, CIC-IT 1433, Nancy (France); Hossu, Gabriela; Felblinger, Jacques [Universite de Lorraine, IADI U947, Nancy (France); INSERM, CIC-IT 1433, Nancy (France); Blum, Alain [CHRU-Nancy Hopital Central, Service d' Imagerie Guilloz, Nancy (France); Braun, Marc [CHRU-Nancy Hopital Central, Service de Neuroradiologie, Nancy (France)

2017-02-15

Assess the use of a volumetric simulation tool for the evaluation of radiology resident MR and CT interpretation skills. Forty-three participants were evaluated with a software allowing the visualisation of multiple volumetric image series. There were 7 medical students, 28 residents and 8 senior radiologists among the participants. Residents were divided into two sub-groups (novice and advanced). The test was composed of 15 exercises on general radiology and lasted 45 min. Participants answered a questionnaire on their experience with the test using a 5-point Likert scale. This study was approved by the dean of the medical school and did not require ethics committee approval. The reliability of the test was good with a Cronbach alpha value of 0.9. Test scores were significantly different in all sub-groups studies (p < 0.0225). The relation between test scores and the year of residency was logarithmic (R{sup 2} = 0.974). Participants agreed that the test reflected their radiological practice (3.9 ± 0.9 on a 5-point scale) and was better than the conventional evaluation methods (4.6 ± 0.5 on a 5-point scale). This software provides a high quality evaluation tool for the assessment of the interpretation skills in radiology residents. (orig.)

Development of an online radiology case review system featuring interactive navigation of volumetric image datasets using advanced visualization techniques

International Nuclear Information System (INIS)

Yang, Hyun Kyung; Kim, Boh Kyoung; Jung, Ju Hyun; Kang, Heung Sik; Lee, Kyoung Ho; Woo, Hyun Soo; Jo, Jae Min; Lee, Min Hee

2015-01-01

To develop an online radiology case review system that allows interactive navigation of volumetric image datasets using advanced visualization techniques. Our Institutional Review Board approved the use of the patient data and waived the need for informed consent. We determined the following system requirements: volumetric navigation, accessibility, scalability, undemanding case management, trainee encouragement, and simulation of a busy practice. The system comprised a case registry server, client case review program, and commercially available cloud-based image viewing system. In the pilot test, we used 30 cases of low-dose abdomen computed tomography for the diagnosis of acute appendicitis. In each case, a trainee was required to navigate through the images and submit answers to the case questions. The trainee was then given the correct answers and key images, as well as the image dataset with annotations on the appendix. After evaluation of all cases, the system displayed the diagnostic accuracy and average review time, and the trainee was asked to reassess the failed cases. The pilot system was deployed successfully in a hands-on workshop course. We developed an online radiology case review system that allows interactive navigation of volumetric image datasets using advanced visualization techniques

Development of an online radiology case review system featuring interactive navigation of volumetric image datasets using advanced visualization techniques

Energy Technology Data Exchange (ETDEWEB)

Yang, Hyun Kyung; Kim, Boh Kyoung; Jung, Ju Hyun; Kang, Heung Sik; Lee, Kyoung Ho [Dept. of Radiology, Seoul National University Bundang Hospital, Seongnam (Korea, Republic of); Woo, Hyun Soo [Dept. of Radiology, SMG-SNU Boramae Medical Center, Seoul (Korea, Republic of); Jo, Jae Min [Dept. of Computer Science and Engineering, Seoul National University, Seoul (Korea, Republic of); Lee, Min Hee [Dept. of Radiology, Soonchunhyang University Bucheon Hospital, Bucheon (Korea, Republic of)

2015-11-15

To develop an online radiology case review system that allows interactive navigation of volumetric image datasets using advanced visualization techniques. Our Institutional Review Board approved the use of the patient data and waived the need for informed consent. We determined the following system requirements: volumetric navigation, accessibility, scalability, undemanding case management, trainee encouragement, and simulation of a busy practice. The system comprised a case registry server, client case review program, and commercially available cloud-based image viewing system. In the pilot test, we used 30 cases of low-dose abdomen computed tomography for the diagnosis of acute appendicitis. In each case, a trainee was required to navigate through the images and submit answers to the case questions. The trainee was then given the correct answers and key images, as well as the image dataset with annotations on the appendix. After evaluation of all cases, the system displayed the diagnostic accuracy and average review time, and the trainee was asked to reassess the failed cases. The pilot system was deployed successfully in a hands-on workshop course. We developed an online radiology case review system that allows interactive navigation of volumetric image datasets using advanced visualization techniques.

Volumetric three-dimensional display system with rasterization hardware

Science.gov (United States)

Favalora, Gregg E.; Dorval, Rick K.; Hall, Deirdre M.; Giovinco, Michael; Napoli, Joshua

2001-06-01

An 8-color multiplanar volumetric display is being developed by Actuality Systems, Inc. It will be capable of utilizing an image volume greater than 90 million voxels, which we believe is the greatest utilizable voxel set of any volumetric display constructed to date. The display is designed to be used for molecular visualization, mechanical CAD, e-commerce, entertainment, and medical imaging. As such, it contains a new graphics processing architecture, novel high-performance line- drawing algorithms, and an API similar to a current standard. Three-dimensional imagery is created by projecting a series of 2-D bitmaps ('image slices') onto a diffuse screen that rotates at 600 rpm. Persistence of vision fuses the slices into a volume-filling 3-D image. A modified three-panel Texas Instruments projector provides slices at approximately 4 kHz, resulting in 8-color 3-D imagery comprised of roughly 200 radially-disposed slices which are updated at 20 Hz. Each slice has a resolution of 768 by 768 pixels, subtending 10 inches. An unusual off-axis projection scheme incorporating tilted rotating optics is used to maintain good focus across the projection screen. The display electronics includes a custom rasterization architecture which converts the user's 3- D geometry data into image slices, as well as 6 Gbits of DDR SDRAM graphics memory.

An analytical phantom for the evaluation of medical flow imaging algorithms

International Nuclear Information System (INIS)

Pashaei, A; Fatouraee, N

2009-01-01

Blood flow characteristics (e.g. velocity, pressure, shear stress, streamline and volumetric flow rate) are effective tools in diagnosis of cardiovascular diseases such as atherosclerotic plaque, aneurism and cardiac muscle failure. Noninvasive estimation of cardiovascular blood flow characteristics is mostly limited to the measurement of velocity components by medical imaging modalities. Once the velocity field is obtained from the images, other flow characteristics within the cardiovascular system can be determined using algorithms relating them to the velocity components. In this work, we propose an analytical flow phantom to evaluate these algorithms accurately. The Navier-Stokes equations are used to derive this flow phantom. The exact solution of these equations obtains analytical expression for the flow characteristics inside the domain. Features such as pulsatility, incompressibility and viscosity of flow are included in a three-dimensional domain. The velocity domain of the resulted system is presented as reference images. These images could be employed to evaluate the performance of different flow characteristic algorithms. In this study, we also present some applications of the obtained phantom. The calculation of pressure domain from velocity data, volumetric flow rate, wall shear stress and particle trace are the characteristics whose algorithms are evaluated here. We also present the application of this phantom in the analysis of noisy and low-resolution images. The presented phantom can be considered as a benchmark test to compare the accuracy of different flow characteristic algorithms.

A method for volumetric imaging in radiotherapy using single x-ray projection

International Nuclear Information System (INIS)

Xu, Yuan; Yan, Hao; Ouyang, Luo; Wang, Jing; Jiang, Steve B.; Jia, Xun; Zhou, Linghong; Cervino, Laura

2015-01-01

Purpose: It is an intriguing problem to generate an instantaneous volumetric image based on the corresponding x-ray projection. The purpose of this study is to develop a new method to achieve this goal via a sparse learning approach. Methods: To extract motion information hidden in projection images, the authors partitioned a projection image into small rectangular patches. The authors utilized a sparse learning method to automatically select patches that have a high correlation with principal component analysis (PCA) coefficients of a lung motion model. A model that maps the patch intensity to the PCA coefficients was built along with the patch selection process. Based on this model, a measured projection can be used to predict the PCA coefficients, which are then further used to generate a motion vector field and hence a volumetric image. The authors have also proposed an intensity baseline correction method based on the partitioned projection, in which the first and the second moments of pixel intensities at a patch in a simulated projection image are matched with those in a measured one via a linear transformation. The proposed method has been validated in both simulated data and real phantom data. Results: The algorithm is able to identify patches that contain relevant motion information such as the diaphragm region. It is found that an intensity baseline correction step is important to remove the systematic error in the motion prediction. For the simulation case, the sparse learning model reduced the prediction error for the first PCA coefficient to 5%, compared to the 10% error when sparse learning was not used, and the 95th percentile error for the predicted motion vector was reduced from 2.40 to 0.92 mm. In the phantom case with a regular tumor motion, the predicted tumor trajectory was successfully reconstructed with a 0.82 mm error for tumor center localization compared to a 1.66 mm error without using the sparse learning method. When the tumor motion

Medical images of patients in voxel structures in high resolution for Monte Carlo simulation

International Nuclear Information System (INIS)

Boia, Leonardo S.; Menezes, Artur F.; Silva, Ademir X.

2011-01-01

This work aims to present a computational process of conversion of tomographic and MRI medical images from patients in voxel structures to an input file, which will be manipulated in Monte Carlo Simulation code for tumor's radiotherapic treatments. The problem's scenario inherent to the patient is simulated by such process, using the volume element (voxel) as a unit of computational tracing. The head's voxel structure geometry has voxels with volumetric dimensions around 1 mm 3 and a population of millions, which helps - in that way, for a realistic simulation and a decrease in image's digital process techniques for adjustments and equalizations. With such additional data from the code, a more critical analysis can be developed in order to determine the volume of the tumor, and the protection, beside the patients' medical images were borrowed by Clinicas Oncologicas Integradas (COI/RJ), joined to the previous performed planning. In order to execute this computational process, SAPDI computational system is used in a digital image process for optimization of data, conversion program Scan2MCNP, which manipulates, processes, and converts the medical images into voxel structures to input files and the graphic visualizer Moritz for the verification of image's geometry placing. (author)

Single-Shot, Volumetrically Illuminated, Three-Dimensional, Tomographic Laser-Induced-Fluorescence Imaging in a Gaseous Free Jet

Science.gov (United States)

2016-04-28

Single-shot, volumetrically illuminated, three- dimensional, tomographic laser-induced- fluorescence imaging in a gaseous free jet Benjamin R. Halls...acquisition; (110.6955) Tomographic imaging ; (110.6960) Tomography; (280.2490) Flow diagnostics; (300.2530) Fluorescence , laser-induced...84 (1983). 2. I. van Cruyningen, A. Lozano, and R. K. Hanson, “Quantitative imaging of concentration by planar laser-induced fluorescence ,” Exp

Scene data fusion: Real-time standoff volumetric gamma-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Barnowski, Ross [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720, United States of America (United States); Haefner, Andrew; Mihailescu, Lucian [Lawrence Berkeley National Lab - Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720, United States of America (United States); Vetter, Kai [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720, United States of America (United States); Lawrence Berkeley National Lab - Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720, United States of America (United States)

2015-11-11

An approach to gamma-ray imaging has been developed that enables near real-time volumetric (3D) imaging of unknown environments thus improving the utility of gamma-ray imaging for source-search and radiation mapping applications. The approach, herein dubbed scene data fusion (SDF), is based on integrating mobile radiation imagers with real-time tracking and scene reconstruction algorithms to enable a mobile mode of operation and 3D localization of gamma-ray sources. A 3D model of the scene, provided in real-time by a simultaneous localization and mapping (SLAM) algorithm, is incorporated into the image reconstruction reducing the reconstruction time and improving imaging performance. The SDF concept is demonstrated in this work with a Microsoft Kinect RGB-D sensor, a real-time SLAM solver, and a cart-based Compton imaging platform comprised of two 3D position-sensitive high purity germanium (HPGe) detectors. An iterative algorithm based on Compton kinematics is used to reconstruct the gamma-ray source distribution in all three spatial dimensions. SDF advances the real-world applicability of gamma-ray imaging for many search, mapping, and verification scenarios by improving the tractiblity of the gamma-ray image reconstruction and providing context for the 3D localization of gamma-ray sources within the environment in real-time.

In vivo evaluation of biosensors volumetric bio-distribution for measurement of metabolic activity by X-ray correlation, fluorescence, Cerenkov image and radioisotope

International Nuclear Information System (INIS)

Ramirez N, G. J.

2016-01-01

The aim of this study was to characterize the in vivo volumetric distribution of three folate based biosensors by different imaging modalities (X-ray, fluorescence, Cerenkov luminescence and radioisotopic imaging) through the development of a tri dimensional (3D) image reconstruction algorithm. The preclinical and multimodal Xtreme imaging system, with a Multimodal Animal Rotation System (Mars), was used to acquire bidimensional (2D) images, which were processed to obtain the 3D reconstruction. Images of mice at different times (biosensor distribution) were simultaneously obtained from the four imaging modalities. The filtered backprojection and inverse Radon transformation were used as main image-processing techniques. In the first instance, the algorithm developed in Mat lab was able to reconstruct in the 3D form the skeleton of the mice under study. Subsequently, the algorithm was able to get the volumetric profiles of "9"9"mTc-Folate-Bombesin (radioisotopic image), "1"7"7Lu-Folate-Bombesin (Cerenkov image), and FolateRSense 680 (fluorescence image) in the tumors and kidneys of the mice. No significant differences were detected between the volumetric quantifications using the standard measurement techniques and the quantifications obtained with the proposal made in this study, nor between the volumetric uptakes in the structures of interest. With the structures reconstructed in the 3D form, the fusion of anatomical (as the skeleton) and functional structures derived from the images of the biosensors uptake was achieved The imaging 3D reconstruction algorithm can be easily extrapolated to different 2D acquisition-type images. This characteristic flexibility of the algorithm developed in this study is an advantage in comparison to similar reconstruction methods. (Author)

Volumetric display using a roof mirror grid array

Science.gov (United States)

Miyazaki, Daisuke; Hirano, Noboru; Maeda, Yuuki; Ohno, Keisuke; Maekawa, Satoshi

2010-02-01

A volumetric display system using a roof mirror grid array (RMGA) is proposed. The RMGA consists of a two-dimensional array of dihedral corner reflectors and forms a real image at a plane-symmetric position. A two-dimensional image formed with a RMGA is moved at thigh speed by a mirror scanner. Cross-sectional images of a three-dimensional object are displayed in accordance with the position of the image plane. A volumetric image can be observed as a stack of the cross-sectional images by high-speed scanning. Image formation by a RMGA is free from aberrations. Moreover, a compact optical system can be constructed because a RMGA doesn't have a focal length. An experimental volumetric display system using a galvanometer mirror and a digital micromirror device was constructed. The formation of a three-dimensional image consisting of 1024 × 768 × 400 voxels is confirmed by the experimental system.

Volumetric Spectroscopic Imaging of Glioblastoma Multiforme Radiation Treatment Volumes

Energy Technology Data Exchange (ETDEWEB)

Parra, N. Andres [Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida (United States); Maudsley, Andrew A. [Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida (United States); Gupta, Rakesh K. [Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, Haryana (India); Ishkanian, Fazilat; Huang, Kris [Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida (United States); Walker, Gail R. [Biostatistics and Bioinformatics Core Resource, Sylvester Cancer Center, University of Miami Miller School of Medicine, Miami, Florida (United States); Padgett, Kyle [Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida (United States); Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida (United States); Roy, Bhaswati [Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, Haryana (India); Panoff, Joseph; Markoe, Arnold [Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida (United States); Stoyanova, Radka, E-mail: RStoyanova@med.miami.edu [Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida (United States)

2014-10-01

Purpose: Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]). Methods and Materials: Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV{sub 46} and CTV{sub 60}, respectively). MTV{sub Cho} and MTV{sub NAA} were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue. Results: The MRSI coverage of the brain was between 70% and 76%. The MTV{sub NAA} were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTV{sub Cho} was outside of the edema (median, 33%) and for some patients it was also outside of the CTV{sub 46} and CTV{sub 60}. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTV{sub Cho} for these patients were outside of CTV{sub 60}. Conclusions: This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on

Composite Match Index with Application of Interior Deformation Field Measurement from Magnetic Resonance Volumetric Images of Human Tissues

Directory of Open Access Journals (Sweden)

Penglin Zhang

2012-01-01

Full Text Available Whereas a variety of different feature-point matching approaches have been reported in computer vision, few feature-point matching approaches employed in images from nonrigid, nonuniform human tissues have been reported. The present work is concerned with interior deformation field measurement of complex human tissues from three-dimensional magnetic resonance (MR volumetric images. To improve the reliability of matching results, this paper proposes composite match index (CMI as the foundation of multimethod fusion methods to increase the reliability of these various methods. Thereinto, we discuss the definition, components, and weight determination of CMI. To test the validity of the proposed approach, it is applied to actual MR volumetric images obtained from a volunteer’s calf. The main result is consistent with the actual condition.

Three-dimensional volumetric display by inclined-plane scanning

Science.gov (United States)

Miyazaki, Daisuke; Eto, Takuma; Nishimura, Yasuhiro; Matsushita, Kenji

2003-05-01

A volumetric display system based on three-dimensional (3-D) scanning that uses an inclined two-dimensional (2-D) image is described. In the volumetric display system a 2-D display unit is placed obliquely in an imaging system into which a rotating mirror is inserted. When the mirror is rotated, the inclined 2-D image is moved laterally. A locus of the moving image can be observed by persistence of vision as a result of the high-speed rotation of the mirror. Inclined cross-sectional images of an object are displayed on the display unit in accordance with the position of the image plane to observe a 3-D image of the object by persistence of vision. Three-dimensional images formed by this display system satisfy all the criteria for stereoscopic vision. We constructed the volumetric display systems using a galvanometer mirror and a vector-scan display unit. In addition, we constructed a real-time 3-D measurement system based on a light section method. Measured 3-D images can be reconstructed in the 3-D display system in real time.

High performance graphics processors for medical imaging applications

International Nuclear Information System (INIS)

Goldwasser, S.M.; Reynolds, R.A.; Talton, D.A.; Walsh, E.S.

1989-01-01

This paper describes a family of high- performance graphics processors with special hardware for interactive visualization of 3D human anatomy. The basic architecture expands to multiple parallel processors, each processor using pipelined arithmetic and logical units for high-speed rendering of Computed Tomography (CT), Magnetic Resonance (MR) and Positron Emission Tomography (PET) data. User-selectable display alternatives include multiple 2D axial slices, reformatted images in sagittal or coronal planes and shaded 3D views. Special facilities support applications requiring color-coded display of multiple datasets (such as radiation therapy planning), or dynamic replay of time- varying volumetric data (such as cine-CT or gated MR studies of the beating heart). The current implementation is a single processor system which generates reformatted images in true real time (30 frames per second), and shaded 3D views in a few seconds per frame. It accepts full scale medical datasets in their native formats, so that minimal preprocessing delay exists between data acquisition and display

Simplifying the exploration of volumetric images: development of a 3D user interface for the radiologist's workplace.

Science.gov (United States)

Teistler, M; Breiman, R S; Lison, T; Bott, O J; Pretschner, D P; Aziz, A; Nowinski, W L

2008-10-01

Volumetric imaging (computed tomography and magnetic resonance imaging) provides increased diagnostic detail but is associated with the problem of navigation through large amounts of data. In an attempt to overcome this problem, a novel 3D navigation tool has been designed and developed that is based on an alternative input device. A 3D mouse allows for simultaneous definition of position and orientation of orthogonal or oblique multiplanar reformatted images or slabs, which are presented within a virtual 3D scene together with the volume-rendered data set and additionally as 2D images. Slabs are visualized with maximum intensity projection, average intensity projection, or standard volume rendering technique. A prototype has been implemented based on PC technology that has been tested by several radiologists. It has shown to be easily understandable and usable after a very short learning phase. Our solution may help to fully exploit the diagnostic potential of volumetric imaging by allowing for a more efficient reading process compared to currently deployed solutions based on conventional mouse and keyboard.

Medical images of patients in voxel structures in high resolution for Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Boia, Leonardo S.; Menezes, Artur F.; Silva, Ademir X., E-mail: lboia@con.ufrj.b, E-mail: ademir@con.ufrj.b [Universidade Federal do Rio de Janeiro (PEN/COPPE/UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-Graduacao de Engenharia. Programa de Engenharia Nuclear; Salmon Junior, Helio A. [Clinicas Oncologicas Integradas (COI), Rio de Janeiro, RJ (Brazil)

2011-07-01

This work aims to present a computational process of conversion of tomographic and MRI medical images from patients in voxel structures to an input file, which will be manipulated in Monte Carlo Simulation code for tumor's radiotherapic treatments. The problem's scenario inherent to the patient is simulated by such process, using the volume element (voxel) as a unit of computational tracing. The head's voxel structure geometry has voxels with volumetric dimensions around 1 mm{sup 3} and a population of millions, which helps - in that way, for a realistic simulation and a decrease in image's digital process techniques for adjustments and equalizations. With such additional data from the code, a more critical analysis can be developed in order to determine the volume of the tumor, and the protection, beside the patients' medical images were borrowed by Clinicas Oncologicas Integradas (COI/RJ), joined to the previous performed planning. In order to execute this computational process, SAPDI computational system is used in a digital image process for optimization of data, conversion program Scan2MCNP, which manipulates, processes, and converts the medical images into voxel structures to input files and the graphic visualizer Moritz for the verification of image's geometry placing. (author)

Image Matrix Processor for Volumetric Computations Final Report CRADA No. TSB-1148-95

Energy Technology Data Exchange (ETDEWEB)

Roberson, G. Patrick [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Browne, Jolyon [Advanced Research & Applications Corporation, Sunnyvale, CA (United States)

2018-01-22

The development of an Image Matrix Processor (IMP) was proposed that would provide an economical means to perform rapid ray-tracing processes on volume "Giga Voxel" data sets. This was a multi-phased project. The objective of the first phase of the IMP project was to evaluate the practicality of implementing a workstation-based Image Matrix Processor for use in volumetric reconstruction and rendering using hardware simulation techniques. Additionally, ARACOR and LLNL worked together to identify and pursue further funding sources to complete a second phase of this project.

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

Energy Technology Data Exchange (ETDEWEB)

Gaudeau, Y

2006-12-15

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

A novel image processing technique for 3D volumetric analysis of severely resorbed alveolar sockets with CBCT.

Science.gov (United States)

Manavella, Valeria; Romano, Federica; Garrone, Federica; Terzini, Mara; Bignardi, Cristina; Aimetti, Mario

2017-06-01

The aim of this study was to present and validate a novel procedure for the quantitative volumetric assessment of extraction sockets that combines cone-beam computed tomography (CBCT) and image processing techniques. The CBCT dataset of 9 severely resorbed extraction sockets was analyzed by means of two image processing software, Image J and Mimics, using manual and automated segmentation techniques. They were also applied on 5-mm spherical aluminum markers of known volume and on a polyvinyl chloride model of one alveolar socket scanned with Micro-CT to test the accuracy. Statistical differences in alveolar socket volume were found between the different methods of volumetric analysis (Psockets showed more accurate results, excellent inter-observer similarity and increased user friendliness. The clinical application of this method enables a three-dimensional evaluation of extraction socket healing after the reconstructive procedures and during the follow-up visits.

as-PSOCT: Volumetric microscopic imaging of human brain architecture and connectivity.

Science.gov (United States)

Wang, Hui; Magnain, Caroline; Wang, Ruopeng; Dubb, Jay; Varjabedian, Ani; Tirrell, Lee S; Stevens, Allison; Augustinack, Jean C; Konukoglu, Ender; Aganj, Iman; Frosch, Matthew P; Schmahmann, Jeremy D; Fischl, Bruce; Boas, David A

2018-01-15

Polarization sensitive optical coherence tomography (PSOCT) with serial sectioning has enabled the investigation of 3D structures in mouse and human brain tissue samples. By using intrinsic optical properties of back-scattering and birefringence, PSOCT reliably images cytoarchitecture, myeloarchitecture and fiber orientations. In this study, we developed a fully automatic serial sectioning polarization sensitive optical coherence tomography (as-PSOCT) system to enable volumetric reconstruction of human brain samples with unprecedented sample size and resolution. The 3.5 μm in-plane resolution and 50 μm through-plane voxel size allow inspection of cortical layers that are a single-cell in width, as well as small crossing fibers. We show the abilities of as-PSOCT in quantifying layer thicknesses of the cerebellar cortex and creating microscopic tractography of intricate fiber networks in the subcortical nuclei and internal capsule regions, all based on volumetric reconstructions. as-PSOCT provides a viable tool for studying quantitative cytoarchitecture and myeloarchitecture and mapping connectivity with microscopic resolution in the human brain. Copyright © 2017 Elsevier Inc. All rights reserved.

Short-term mechanisms influencing volumetric brain dynamics

Directory of Open Access Journals (Sweden)

Nikki Dieleman

2017-01-01

Full Text Available With the use of magnetic resonance imaging (MRI and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist. When we focus on short-term changes of the brain, changes may be either physiological or pathological. As such determining the cause of volumetric dynamics of the brain is essential. Additionally for an accurate interpretation of longitudinal brain volume measures by means of neurodegeneration, knowledge about the short-term changes is needed. Therefore, in this review, we discuss the possible mechanisms influencing brain volumes on a short-term basis and set-out a framework of MRI techniques to be used for volumetric changes as well as the used analysis tools. 3D T1-weighted images are the images of choice when it comes to MRI of brain volume. These images are excellent to determine brain volume and can be used together with an analysis tool to determine the degree of volume change. Mechanisms that decrease global brain volume are: fluid restriction, evening MRI measurements, corticosteroids, antipsychotics and short-term effects of pathological processes like Alzheimer's disease, hypertension and Diabetes mellitus type II. Mechanisms increasing the brain volume include fluid intake, morning MRI measurements, surgical revascularization and probably medications like anti-inflammatory drugs and anti-hypertensive medication. Exercise was found to have no effect on brain volume on a short-term basis, which may imply that dehydration caused by exercise differs from dehydration by fluid restriction. In the upcoming years, attention should be directed towards studies investigating physiological short-term changes within the light of long-term pathological changes. Ultimately this may lead to a better understanding of the physiological short-term effects of

Very high frame rate volumetric integration of depth images on mobile devices.

Science.gov (United States)

Kähler, Olaf; Adrian Prisacariu, Victor; Yuheng Ren, Carl; Sun, Xin; Torr, Philip; Murray, David

2015-11-01

Volumetric methods provide efficient, flexible and simple ways of integrating multiple depth images into a full 3D model. They provide dense and photorealistic 3D reconstructions, and parallelised implementations on GPUs achieve real-time performance on modern graphics hardware. To run such methods on mobile devices, providing users with freedom of movement and instantaneous reconstruction feedback, remains challenging however. In this paper we present a range of modifications to existing volumetric integration methods based on voxel block hashing, considerably improving their performance and making them applicable to tablet computer applications. We present (i) optimisations for the basic data structure, and its allocation and integration; (ii) a highly optimised raycasting pipeline; and (iii) extensions to the camera tracker to incorporate IMU data. In total, our system thus achieves frame rates up 47 Hz on a Nvidia Shield Tablet and 910 Hz on a Nvidia GTX Titan XGPU, or even beyond 1.1 kHz without visualisation.

Probabilistic atlas-guided eigen-organ method for simultaneous bounding box estimation of multiple organs in volumetric CT images

International Nuclear Information System (INIS)

Yao, Cong; Wada, Takashige; Shimizu, Akinobu; Kobatake, Hidefumi; Nawano, Shigeru

2006-01-01

We propose an approach for the simultaneous bounding box estimation of multiple organs in volumetric CT images. Local eigen-organ spaces are constructed for different types of training organs, and a global eigen-space, which describes the spatial relationships between the organs, is also constructed. Each volume of interest in the abdominal CT image is projected into the local eigen-organ spaces, and several candidate locations are determined. The final selection of the organ locations is made by projecting the set of candidate locations into the global eigen-space. A probabilistic atlas of organs is used to eliminate locations with low probability and to guide the selection of candidate locations. Evaluation by the leave-one-out method using 10 volumetric abdominal CT images showed that the proposed method provided an average accuracy of 80.38% for 11 different organ types. (author)

Single-chip CMUT-on-CMOS front-end system for real-time volumetric IVUS and ICE imaging.

Science.gov (United States)

Gurun, Gokce; Tekes, Coskun; Zahorian, Jaime; Xu, Toby; Satir, Sarp; Karaman, Mustafa; Hasler, Jennifer; Degertekin, F Levent

2014-02-01

Intravascular ultrasound (IVUS) and intracardiac echography (ICE) catheters with real-time volumetric ultrasound imaging capability can provide unique benefits to many interventional procedures used in the diagnosis and treatment of coronary and structural heart diseases. Integration of capacitive micromachined ultrasonic transducer (CMUT) arrays with front-end electronics in single-chip configuration allows for implementation of such catheter probes with reduced interconnect complexity, miniaturization, and high mechanical flexibility. We implemented a single-chip forward-looking (FL) ultrasound imaging system by fabricating a 1.4-mm-diameter dual-ring CMUT array using CMUT-on-CMOS technology on a front-end IC implemented in 0.35-μm CMOS process. The dual-ring array has 56 transmit elements and 48 receive elements on two separate concentric annular rings. The IC incorporates a 25-V pulser for each transmitter and a low-noise capacitive transimpedance amplifier (TIA) for each receiver, along with digital control and smart power management. The final shape of the silicon chip is a 1.5-mm-diameter donut with a 430-μm center hole for a guide wire. The overall front-end system requires only 13 external connections and provides 4 parallel RF outputs while consuming an average power of 20 mW. We measured RF A-scans from the integrated single- chip array which show full functionality at 20.1 MHz with 43% fractional bandwidth. We also tested and demonstrated the image quality of the system on a wire phantom and an ex vivo chicken heart sample. The measured axial and lateral point resolutions are 92 μm and 251 μm, respectively. We successfully acquired volumetric imaging data from the ex vivo chicken heart at 60 frames per second without any signal averaging. These demonstrative results indicate that single-chip CMUT-on-CMOS systems have the potential to produce realtime volumetric images with image quality and speed suitable for catheter-based clinical applications.

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

Energy Technology Data Exchange (ETDEWEB)

Gaudeau, Y

2006-12-15

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

Volumetric full-range magnetomotive optical coherence tomography

Science.gov (United States)

Ahmad, Adeel; Kim, Jongsik; Shemonski, Nathan D.; Marjanovic, Marina; Boppart, Stephen A.

2014-01-01

Abstract. Magnetomotive optical coherence tomography (MM-OCT) can be utilized to spatially localize the presence of magnetic particles within tissues or organs. These magnetic particle-containing regions are detected by using the capability of OCT to measure small-scale displacements induced by the activation of an external electromagnet coil typically driven by a harmonic excitation signal. The constraints imposed by the scanning schemes employed and tissue viscoelastic properties limit the speed at which conventional MM-OCT data can be acquired. Realizing that electromagnet coils can be designed to exert MM force on relatively large tissue volumes (comparable or larger than typical OCT imaging fields of view), we show that an order-of-magnitude improvement in three-dimensional (3-D) MM-OCT imaging speed can be achieved by rapid acquisition of a volumetric scan during the activation of the coil. Furthermore, we show volumetric (3-D) MM-OCT imaging over a large imaging depth range by combining this volumetric scan scheme with full-range OCT. Results with tissue equivalent phantoms and a biological tissue are shown to demonstrate this technique. PMID:25472770

Operating scheme for the light-emitting diode array of a volumetric display that exhibits multiple full-color dynamic images

Science.gov (United States)

Hirayama, Ryuji; Shiraki, Atsushi; Nakayama, Hirotaka; Kakue, Takashi; Shimobaba, Tomoyoshi; Ito, Tomoyoshi

2017-07-01

We designed and developed a control circuit for a three-dimensional (3-D) light-emitting diode (LED) array to be used in volumetric displays exhibiting full-color dynamic 3-D images. The circuit was implemented on a field-programmable gate array; therefore, pulse-width modulation, which requires high-speed processing, could be operated in real time. We experimentally evaluated the developed system by measuring the luminance of an LED with varying input and confirmed that the system works appropriately. In addition, we demonstrated that the volumetric display exhibits different full-color dynamic two-dimensional images in two orthogonal directions. Each of the exhibited images could be obtained only from the prescribed viewpoint. Such directional characteristics of the system are beneficial for applications, including digital signage, security systems, art, and amusement.

Parkinson's disease: diagnostic utility of volumetric imaging

Energy Technology Data Exchange (ETDEWEB)

Lin, Wei-Che; Chen, Meng-Hsiang [Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Department of Diagnostic Radiology, Kaohsiung (China); Chou, Kun-Hsien [National Yang-Ming University, Brain Research Center, Taipei (China); Lee, Pei-Lin [National Yang-Ming University, Department of Biomedical Imaging and Radiological Sciences, Taipei (China); Tsai, Nai-Wen; Lu, Cheng-Hsien [Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Department of Neurology, Kaohsiung (China); Chen, Hsiu-Ling [Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Department of Diagnostic Radiology, Kaohsiung (China); National Yang-Ming University, Department of Biomedical Imaging and Radiological Sciences, Taipei (China); Hsu, Ai-Ling [National Taiwan University, Institute of Biomedical Electronics and Bioinformatics, Taipei (China); Huang, Yung-Cheng [Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Department of Nuclear Medicine, Kaohsiung (China); Lin, Ching-Po [National Yang-Ming University, Brain Research Center, Taipei (China); National Yang-Ming University, Department of Biomedical Imaging and Radiological Sciences, Taipei (China)

2017-04-15

This paper aims to examine the effectiveness of structural imaging as an aid in the diagnosis of Parkinson's disease (PD). High-resolution T{sub 1}-weighted magnetic resonance imaging was performed in 72 patients with idiopathic PD (mean age, 61.08 years) and 73 healthy subjects (mean age, 58.96 years). The whole brain was parcellated into 95 regions of interest using composite anatomical atlases, and region volumes were calculated. Three diagnostic classifiers were constructed using binary multiple logistic regression modeling: the (i) basal ganglion prior classifier, (ii) data-driven classifier, and (iii) basal ganglion prior/data-driven hybrid classifier. Leave-one-out cross validation was used to unbiasedly evaluate the predictive accuracy of imaging features. Pearson's correlation analysis was further performed to correlate outcome measurement using the best PD classifier with disease severity. Smaller volume in susceptible regions is diagnostic for Parkinson's disease. Compared with the other two classifiers, the basal ganglion prior/data-driven hybrid classifier had the highest diagnostic reliability with a sensitivity of 74%, specificity of 75%, and accuracy of 74%. Furthermore, outcome measurement using this classifier was associated with disease severity. Brain structural volumetric analysis with multiple logistic regression modeling can be a complementary tool for diagnosing PD. (orig.)

Assessment of pituitary adenoma volumetric change using longitudinal MR image registration

International Nuclear Information System (INIS)

Ringstad, Geir Andre; Hald, John K.; Emblem, Kyrre Eeg; Holland, Dominic; Dale, Anders M.; Bjornerud, Atle

2012-01-01

Change detection is a crucial factor in monitoring of slowly evolving pathologies. The objective of the study was to test a semi-automatic method applied on longitudinal MRI monitoring of volume change in pituitary macroadenomas. The proposed method is based on a visual comparison of geometrically corrected, co-registered, intensity-normalized contrast-enhanced (CE) 3D GRE T1-weighted images. Qualitative volume changes based on this applied method were compared with experts' readings of conventional pre- and post-CE 2D T1-weighted images. Magnetic resonance (MR) imaging was performed two to four times in 13 patients with a total combination of 29 time points. Compared to conventional 2D MR readings, a diagnosis of tumor growth (yes/no) was changed in 5 of 13 patients (38%) at 9 of the 29 combinations of time points (31%) using the 3D-based semi-automatic method. With manual tumor tracings as reference, McNemar's test showed a significant difference between the two methods. Visual comparison of geometrically corrected, intensity-normalized, and affine-aligned longitudinal 3D images may enable more accurate assessment of qualitative volumetric change in pituitary adenomas than conventional reading of 2D images. (orig.)

Volumetric fluorescence retinal imaging in vivo over a 30-degree field of view by oblique scanning laser ophthalmoscopy (oSLO).

Science.gov (United States)

Zhang, Lei; Song, Weiye; Shao, Di; Zhang, Sui; Desai, Manishi; Ness, Steven; Roy, Sayon; Yi, Ji

2018-01-01

While fluorescent contrast is widely used in ophthalmology, three-dimensional (3D) fluorescence retinal imaging over a large field of view (FOV) has been challenging. In this paper, we describe a novel oblique scanning laser ophthalmoscopy (oSLO) technique that provides 3D volumetric fluorescence retinal imaging with only one raster scan. The technique utilizes scanned oblique illumination and angled detection to obtain fluorescent cross-sectional images, analogous to optical coherence tomography (OCT) line scans (or B-scans). By breaking the coaxial optical alignment used in conventional retinal imaging modalities, depth resolution is drastically improved. To demonstrate the capability of oSLO, we have performed in vivo volumetric fluorescein angiography (FA) of the rat retina with ~25μm depth resolution and over a 30° FOV. Using depth segmentation, oSLO can obtain high contrast images of the microvasculature down to single capillaries in 3D. The multi-modal nature of oSLO also allows for seamless combination with simultaneous OCT angiography.

A three-dimensional-weighted cone beam filtered backprojection (CB-FBP) algorithm for image reconstruction in volumetric CT-helical scanning

International Nuclear Information System (INIS)

Tang Xiangyang; Hsieh Jiang; Nilsen, Roy A; Dutta, Sandeep; Samsonov, Dmitry; Hagiwara, Akira

2006-01-01

Based on the structure of the original helical FDK algorithm, a three-dimensional (3D)-weighted cone beam filtered backprojection (CB-FBP) algorithm is proposed for image reconstruction in volumetric CT under helical source trajectory. In addition to its dependence on view and fan angles, the 3D weighting utilizes the cone angle dependency of a ray to improve reconstruction accuracy. The 3D weighting is ray-dependent and the underlying mechanism is to give a favourable weight to the ray with the smaller cone angle out of a pair of conjugate rays but an unfavourable weight to the ray with the larger cone angle out of the conjugate ray pair. The proposed 3D-weighted helical CB-FBP reconstruction algorithm is implemented in the cone-parallel geometry that can improve noise uniformity and image generation speed significantly. Under the cone-parallel geometry, the filtering is naturally carried out along the tangential direction of the helical source trajectory. By exploring the 3D weighting's dependence on cone angle, the proposed helical 3D-weighted CB-FBP reconstruction algorithm can provide significantly improved reconstruction accuracy at moderate cone angle and high helical pitches. The 3D-weighted CB-FBP algorithm is experimentally evaluated by computer-simulated phantoms and phantoms scanned by a diagnostic volumetric CT system with a detector dimension of 64 x 0.625 mm over various helical pitches. The computer simulation study shows that the 3D weighting enables the proposed algorithm to reach reconstruction accuracy comparable to that of exact CB reconstruction algorithms, such as the Katsevich algorithm, under a moderate cone angle (4 deg.) and various helical pitches. Meanwhile, the experimental evaluation using the phantoms scanned by a volumetric CT system shows that the spatial resolution along the z-direction and noise characteristics of the proposed 3D-weighted helical CB-FBP reconstruction algorithm are maintained very well in comparison to the FDK

Effects of defect pixel correction algorithms for x-ray detectors on image quality in planar projection and volumetric CT data sets

International Nuclear Information System (INIS)

Kuttig, Jan; Steiding, Christian; Hupfer, Martin; Karolczak, Marek; Kolditz, Daniel

2015-01-01

In this study we compared various defect pixel correction methods for reducing artifact appearance within projection images used for computed tomography (CT) reconstructions.Defect pixel correction algorithms were examined with respect to their artifact behaviour within planar projection images as well as in volumetric CT reconstructions. We investigated four algorithms: nearest neighbour, linear and adaptive linear interpolation, and a frequency-selective spectral-domain approach.To characterise the quality of each algorithm in planar image data, we inserted line defects of varying widths and orientations into images. The structure preservation of each algorithm was analysed by corrupting and correcting the image of a slit phantom pattern and by evaluating its line spread function (LSF). The noise preservation was assessed by interpolating corrupted flat images and estimating the noise power spectrum (NPS) of the interpolated region.For the volumetric investigations, we examined the structure and noise preservation within a structured aluminium foam, a mid-contrast cone-beam phantom and a homogeneous Polyurethane (PUR) cylinder.The frequency-selective algorithm showed the best structure and noise preservation for planar data of the correction methods tested. For volumetric data it still showed the best noise preservation, whereas the structure preservation was outperformed by the linear interpolation.The frequency-selective spectral-domain approach in the correction of line defects is recommended for planar image data, but its abilities within high-contrast volumes are restricted. In that case, the application of a simple linear interpolation might be the better choice to correct line defects within projection images used for CT. (paper)

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...

Volumetric expiratory high-resolution CT of the lung

International Nuclear Information System (INIS)

Nishino, Mizuki; Hatabu, Hiroto

2004-01-01

We developed a volumetric expiratory high-resolution CT (HRCT) protocol that provides combined inspiratory and expiratory volumetric imaging of the lung without increasing radiation exposure, and conducted a preliminary feasibility assessment of this protocol to evaluate diffuse lung disease with small airway abnormalities. The volumetric expiratory high-resolution CT increased the detectability of the conducting airway to the areas of air trapping (P<0.0001), and added significant information about extent and distribution of air trapping (P<0.0001)

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

Assessment of pituitary adenoma volumetric change using longitudinal MR image registration

Energy Technology Data Exchange (ETDEWEB)

Ringstad, Geir Andre; Hald, John K. [Oslo University Hospital-Rikshospitalet, Clinic for Imaging and Intervention, Oslo (Norway); Emblem, Kyrre Eeg [Oslo University Hospital-Rikshospitalet, Department of Medical Physics, Oslo (Norway); Oslo University Hospital-Rikshospitalet, The Interventional Centre, Oslo (Norway); Holland, Dominic [University of California, Department of Neurosciences, San Diego, CA (United States); Dale, Anders M. [University of California, Department of Neurosciences, San Diego, CA (United States); University of California, Department of Radiology, San Diego, CA (United States); Bjornerud, Atle [Oslo University Hospital-Rikshospitalet, Department of Medical Physics, Oslo (Norway); University of Oslo, Department of Physics, Oslo (Norway)

2012-05-15

Change detection is a crucial factor in monitoring of slowly evolving pathologies. The objective of the study was to test a semi-automatic method applied on longitudinal MRI monitoring of volume change in pituitary macroadenomas. The proposed method is based on a visual comparison of geometrically corrected, co-registered, intensity-normalized contrast-enhanced (CE) 3D GRE T1-weighted images. Qualitative volume changes based on this applied method were compared with experts' readings of conventional pre- and post-CE 2D T1-weighted images. Magnetic resonance (MR) imaging was performed two to four times in 13 patients with a total combination of 29 time points. Compared to conventional 2D MR readings, a diagnosis of tumor growth (yes/no) was changed in 5 of 13 patients (38%) at 9 of the 29 combinations of time points (31%) using the 3D-based semi-automatic method. With manual tumor tracings as reference, McNemar's test showed a significant difference between the two methods. Visual comparison of geometrically corrected, intensity-normalized, and affine-aligned longitudinal 3D images may enable more accurate assessment of qualitative volumetric change in pituitary adenomas than conventional reading of 2D images. (orig.)

Selective plane illumination microscopy (SPIM) with time-domain fluorescence lifetime imaging microscopy (FLIM) for volumetric measurement of cleared mouse brain samples

Science.gov (United States)

Funane, Tsukasa; Hou, Steven S.; Zoltowska, Katarzyna Marta; van Veluw, Susanne J.; Berezovska, Oksana; Kumar, Anand T. N.; Bacskai, Brian J.

2018-05-01

We have developed an imaging technique which combines selective plane illumination microscopy with time-domain fluorescence lifetime imaging microscopy (SPIM-FLIM) for three-dimensional volumetric imaging of cleared mouse brains with micro- to mesoscopic resolution. The main features of the microscope include a wavelength-adjustable pulsed laser source (Ti:sapphire) (near-infrared) laser, a BiBO frequency-doubling photonic crystal, a liquid chamber, an electrically focus-tunable lens, a cuvette based sample holder, and an air (dry) objective lens. The performance of the system was evaluated with a lifetime reference dye and micro-bead phantom measurements. Intensity and lifetime maps of three-dimensional human embryonic kidney (HEK) cell culture samples and cleared mouse brain samples expressing green fluorescent protein (GFP) (donor only) and green and red fluorescent protein [positive Förster (fluorescence) resonance energy transfer] were acquired. The results show that the SPIM-FLIM system can be used for sample sizes ranging from single cells to whole mouse organs and can serve as a powerful tool for medical and biological research.

Semiautomatic segmentation of liver metastases on volumetric CT images

International Nuclear Information System (INIS)

Yan, Jiayong; Schwartz, Lawrence H.; Zhao, Binsheng

2015-01-01

Purpose: Accurate segmentation and quantification of liver metastases on CT images are critical to surgery/radiation treatment planning and therapy response assessment. To date, there are no reliable methods to perform such segmentation automatically. In this work, the authors present a method for semiautomatic delineation of liver metastases on contrast-enhanced volumetric CT images. Methods: The first step is to manually place a seed region-of-interest (ROI) in the lesion on an image. This ROI will (1) serve as an internal marker and (2) assist in automatically identifying an external marker. With these two markers, lesion contour on the image can be accurately delineated using traditional watershed transformation. Density information will then be extracted from the segmented 2D lesion and help determine the 3D connected object that is a candidate of the lesion volume. The authors have developed a robust strategy to automatically determine internal and external markers for marker-controlled watershed segmentation. By manually placing a seed region-of-interest in the lesion to be delineated on a reference image, the method can automatically determine dual threshold values to approximately separate the lesion from its surrounding structures and refine the thresholds from the segmented lesion for the accurate segmentation of the lesion volume. This method was applied to 69 liver metastases (1.1–10.3 cm in diameter) from a total of 15 patients. An independent radiologist manually delineated all lesions and the resultant lesion volumes served as the “gold standard” for validation of the method’s accuracy. Results: The algorithm received a median overlap, overestimation ratio, and underestimation ratio of 82.3%, 6.0%, and 11.5%, respectively, and a median average boundary distance of 1.2 mm. Conclusions: Preliminary results have shown that volumes of liver metastases on contrast-enhanced CT images can be accurately estimated by a semiautomatic segmentation

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.

Quantification of smoothing requirement for 3D optic flow calculation of volumetric images

DEFF Research Database (Denmark)

Bab-Hadiashar, Alireza; Tennakoon, Ruwan B.; de Bruijne, Marleen

2013-01-01

Complexities of dynamic volumetric imaging challenge the available computer vision techniques on a number of different fronts. This paper examines the relationship between the estimation accuracy and required amount of smoothness for a general solution from a robust statistics perspective. We show...... that a (surprisingly) small amount of local smoothing is required to satisfy both the necessary and sufficient conditions for accurate optic flow estimation. This notion is called 'just enough' smoothing, and its proper implementation has a profound effect on the preservation of local information in processing 3D...... dynamic scans. To demonstrate the effect of 'just enough' smoothing, a robust 3D optic flow method with quantized local smoothing is presented, and the effect of local smoothing on the accuracy of motion estimation in dynamic lung CT images is examined using both synthetic and real image sequences...

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.)

Simplifying the Exploration of Volumetric Images: Development of a 3D User Interface for the Radiologist’s Workplace

OpenAIRE

Teistler, M.; Breiman, R. S.; Lison, T.; Bott, O. J.; Pretschner, D. P.; Aziz, A.; Nowinski, W. L.

2007-01-01

Volumetric imaging (computed tomography and magnetic resonance imaging) provides increased diagnostic detail but is associated with the problem of navigation through large amounts of data. In an attempt to overcome this problem, a novel 3D navigation tool has been designed and developed that is based on an alternative input device. A 3D mouse allows for simultaneous definition of position and orientation of orthogonal or oblique multiplanar reformatted images or slabs, which are presented wit...

Systematic Parameterization, Storage, and Representation of Volumetric DICOM Data.

Science.gov (United States)

Fischer, Felix; Selver, M Alper; Gezer, Sinem; Dicle, Oğuz; Hillen, Walter

Tomographic medical imaging systems produce hundreds to thousands of slices, enabling three-dimensional (3D) analysis. Radiologists process these images through various tools and techniques in order to generate 3D renderings for various applications, such as surgical planning, medical education, and volumetric measurements. To save and store these visualizations, current systems use snapshots or video exporting, which prevents further optimizations and requires the storage of significant additional data. The Grayscale Softcopy Presentation State extension of the Digital Imaging and Communications in Medicine (DICOM) standard resolves this issue for two-dimensional (2D) data by introducing an extensive set of parameters, namely 2D Presentation States (2DPR), that describe how an image should be displayed. 2DPR allows storing these parameters instead of storing parameter applied images, which cause unnecessary duplication of the image data. Since there is currently no corresponding extension for 3D data, in this study, a DICOM-compliant object called 3D presentation states (3DPR) is proposed for the parameterization and storage of 3D medical volumes. To accomplish this, the 3D medical visualization process is divided into four tasks, namely pre-processing, segmentation, post-processing, and rendering. The important parameters of each task are determined. Special focus is given to the compression of segmented data, parameterization of the rendering process, and DICOM-compliant implementation of the 3DPR object. The use of 3DPR was tested in a radiology department on three clinical cases, which require multiple segmentations and visualizations during the workflow of radiologists. The results show that 3DPR can effectively simplify the workload of physicians by directly regenerating 3D renderings without repeating intermediate tasks, increase efficiency by preserving all user interactions, and provide efficient storage as well as transfer of visualized data.

A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

Science.gov (United States)

Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

2017-03-01

Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

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

Optimized T1- and T2-weighted volumetric brain imaging as a diagnostic tool in very preterm neonates

International Nuclear Information System (INIS)

Nossin-Manor, Revital; Chung, Andrew D.; Morris, Drew; Thomas, Bejoy; Shroff, Manohar M.; Soares-Fernandes, Joao P.; Cheng, Hai-Ling M.; Whyte, Hilary E.A.; Taylor, Margot J.; Sled, John G.

2011-01-01

T1- and T2-W MR sequences used for obtaining diagnostic information and morphometric measurements in the neonatal brain are frequently acquired using different imaging protocols. Optimizing one protocol for obtaining both kinds of information is valuable. To determine whether high-resolution T1- and T2-W volumetric sequences optimized for preterm brain imaging could provide both diagnostic and morphometric value. Thirty preterm neonates born between 24 and 32 weeks' gestational age were scanned during the first 2 weeks after birth. T1- and T2-W high-resolution sequences were optimized in terms of signal-to-noise ratio, contrast-to-noise ratio and scan time and compared to conventional spin-echo-based sequences. No differences were found between conventional and high-resolution T1-W sequences for diagnostic confidence, image quality and motion artifacts. A preference for conventional over high-resolution T2-W sequences for image quality was observed. High-resolution T1 images provided better delineation of thalamic myelination and the superior temporal sulcus. No differences were found for detection of myelination and sulcation using conventional and high-resolution T2-W images. High-resolution T1- and T2-W volumetric sequences can be used in clinical MRI in the very preterm brain to provide both diagnostic and morphometric information. (orig.)

Automatic Prostate Tracking and Motion Assessment in Volumetric Modulated Arc Therapy With an Electronic Portal Imaging Device

International Nuclear Information System (INIS)

Azcona, Juan Diego; Li, Ruijiang; Mok, Edward; Hancock, Steven; Xing, Lei

2013-01-01

Purpose: To assess the prostate intrafraction motion in volumetric modulated arc therapy treatments using cine megavoltage (MV) images acquired with an electronic portal imaging device (EPID). Methods and Materials: Ten prostate cancer patients were treated with volumetric modulated arc therapy using a Varian TrueBeam linear accelerator equipped with an EPID for acquiring cine MV images during treatment. Cine MV images acquisition was scheduled for single or multiple treatment fractions (between 1 and 8). A novel automatic fiducial detection algorithm that can handle irregular multileaf collimator apertures, field edges, fast leaf and gantry movement, and MV image noise and artifacts in patient anatomy was used. All sets of images (approximately 25,000 images in total) were analyzed to measure the positioning accuracy of implanted fiducial markers and assess the prostate movement. Results: Prostate motion can vary greatly in magnitude among different patients. Different motion patterns were identified, showing its unpredictability. The mean displacement and standard deviation of the intrafraction motion was generally less than 2.0 ± 2.0 mm in each of the spatial directions. In certain patients, however, the percentage of the treatment time in which the prostate is displaced more than 5 mm from its planned position in at least 1 spatial direction was 10% or more. The maximum prostate displacement observed was 13.3 mm. Conclusion: Prostate tracking and motion assessment was performed with MV imaging and an EPID. The amount of prostate motion observed suggests that patients will benefit from its real-time monitoring. Megavoltage imaging can provide the basis for real-time prostate tracking using conventional linear accelerators

Potential Applications of Flat-Panel Volumetric CT in Morphologic, Functional Small Animal Imaging

Directory of Open Access Journals (Sweden)

Susanne Greschus

2005-08-01

Full Text Available Noninvasive radiologic imaging has recently gained considerable interest in basic, preclinical research for monitoring disease progression, therapeutic efficacy. In this report, we introduce flat-panel volumetric computed tomography (fpVCT as a powerful new tool for noninvasive imaging of different organ systems in preclinical research. The three-dimensional visualization that is achieved by isotropic high-resolution datasets is illustrated for the skeleton, chest, abdominal organs, brain of mice. The high image quality of chest scans enables the visualization of small lung nodules in an orthotopic lung cancer model, the reliable imaging of therapy side effects such as lung fibrosis. Using contrast-enhanced scans, fpVCT displayed the vascular trees of the brain, liver, kidney down to the subsegmental level. Functional application of fpVCT in dynamic contrast-enhanced scans of the rat brain delivered physiologically reliable data of perfusion, tissue blood volume. Beyond scanning of small animal models as demonstrated here, fpVCT provides the ability to image animals up to the size of primates.

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.

High definition ultrasound imaging for battlefield medical applications

Energy Technology Data Exchange (ETDEWEB)

Kwok, K.S.; Morimoto, A.K.; Kozlowski, D.M.; Krumm, J.C.; Dickey, F.M. [Sandia National Labs., Albuquerque, NM (United States); Rogers, B; Walsh, N. [Texas Univ. Health Science Center, San Antonio, TX (United States)

1996-06-23

A team has developed an improved resolution ultrasound system for low cost diagnostics. This paper describes the development of an ultrasound based imaging system capable of generating 3D images showing surface and subsurface tissue and bone structures. We include results of a comparative study between images obtained from X-Ray Computed Tomography (CT) and ultrasound. We found that the quality of ultrasound images compares favorably with those from CT. Volumetric and surface data extracted from these images were within 7% of the range between ultrasound and CT scans. We also include images of porcine abdominal scans from two different sets of animal trials.

Conversion of a Surface Model of a Structure of Interest into a Volume Model for Medical Image Retrieval

Directory of Open Access Journals (Sweden)

Sarmad ISTEPHAN

2015-06-01

Full Text Available Volumetric medical image datasets contain vital information for noninvasive diagnosis, treatment planning and prognosis. However, direct and unlimited query of such datasets is hindered due to the unstructured nature of the imaging data. This study is a step towards the unlimited query of medical image datasets by focusing on specific Structures of Interest (SOI. A requirement in achieving this objective is having both the surface and volume models of the SOI. However, typically, only the surface model is available. Therefore, this study focuses on creating a fast method to convert a surface model to a volume model. Three methods (1D, 2D and 3D are proposed and evaluated using simulated and real data of Deep Perisylvian Area (DPSA within the human brain. The 1D method takes 80 msec for DPSA model; about 4 times faster than 2D method and 7.4 fold faster than 3D method, with over 97% accuracy. The proposed 1D method is feasible for surface to volume conversion in computer aided diagnosis, treatment planning and prognosis systems containing large amounts of unstructured medical images.

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.

Exploring interaction with 3D volumetric displays

Science.gov (United States)

Grossman, Tovi; Wigdor, Daniel; Balakrishnan, Ravin

2005-03-01

Volumetric displays generate true volumetric 3D images by actually illuminating points in 3D space. As a result, viewing their contents is similar to viewing physical objects in the real world. These displays provide a 360 degree field of view, and do not require the user to wear hardware such as shutter glasses or head-trackers. These properties make them a promising alternative to traditional display systems for viewing imagery in 3D. Because these displays have only recently been made available commercially (e.g., www.actuality-systems.com), their current use tends to be limited to non-interactive output-only display devices. To take full advantage of the unique features of these displays, however, it would be desirable if the 3D data being displayed could be directly interacted with and manipulated. We investigate interaction techniques for volumetric display interfaces, through the development of an interactive 3D geometric model building application. While this application area itself presents many interesting challenges, our focus is on the interaction techniques that are likely generalizable to interactive applications for other domains. We explore a very direct style of interaction where the user interacts with the virtual data using direct finger manipulations on and around the enclosure surrounding the displayed 3D volumetric image.

A volumetric three-dimensional digital light photoactivatable dye display

Science.gov (United States)

Patel, Shreya K.; Cao, Jian; Lippert, Alexander R.

2017-07-01

Volumetric three-dimensional displays offer spatially accurate representations of images with a 360° view, but have been difficult to implement due to complex fabrication requirements. Herein, a chemically enabled volumetric 3D digital light photoactivatable dye display (3D Light PAD) is reported. The operating principle relies on photoactivatable dyes that become reversibly fluorescent upon illumination with ultraviolet light. Proper tuning of kinetics and emission wavelengths enables the generation of a spatial pattern of fluorescent emission at the intersection of two structured light beams. A first-generation 3D Light PAD was fabricated using the photoactivatable dye N-phenyl spirolactam rhodamine B, a commercial picoprojector, an ultraviolet projector and a custom quartz imaging chamber. The system displays a minimum voxel size of 0.68 mm3, 200 μm resolution and good stability over repeated `on-off' cycles. A range of high-resolution 3D images and animations can be projected, setting the foundation for widely accessible volumetric 3D displays.

Volumetric 3D display using a DLP projection engine

Science.gov (United States)

Geng, Jason

2012-03-01

In this article, we describe a volumetric 3D display system based on the high speed DLPTM (Digital Light Processing) projection engine. Existing two-dimensional (2D) flat screen displays often lead to ambiguity and confusion in high-dimensional data/graphics presentation due to lack of true depth cues. Even with the help of powerful 3D rendering software, three-dimensional (3D) objects displayed on a 2D flat screen may still fail to provide spatial relationship or depth information correctly and effectively. Essentially, 2D displays have to rely upon capability of human brain to piece together a 3D representation from 2D images. Despite the impressive mental capability of human visual system, its visual perception is not reliable if certain depth cues are missing. In contrast, volumetric 3D display technologies to be discussed in this article are capable of displaying 3D volumetric images in true 3D space. Each "voxel" on a 3D image (analogous to a pixel in 2D image) locates physically at the spatial position where it is supposed to be, and emits light from that position toward omni-directions to form a real 3D image in 3D space. Such a volumetric 3D display provides both physiological depth cues and psychological depth cues to human visual system to truthfully perceive 3D objects. It yields a realistic spatial representation of 3D objects and simplifies our understanding to the complexity of 3D objects and spatial relationship among them.

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

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.

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 ...

A Technique for Generating Volumetric Cine-Magnetic Resonance Imaging

International Nuclear Information System (INIS)

Harris, Wendy; Ren, Lei; Cai, Jing; Zhang, You; Chang, Zheng; Yin, Fang-Fang

2016-01-01

Purpose: The purpose of this study was to develop a techique to generate on-board volumetric cine-magnetic resonance imaging (VC-MRI) using patient prior images, motion modeling, and on-board 2-dimensional cine MRI. Methods and Materials: One phase of a 4-dimensional MRI acquired during patient simulation is used as patient prior images. Three major respiratory deformation patterns of the patient are extracted from 4-dimensional MRI based on principal-component analysis. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI. The deformation field is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by the data fidelity constraint using the acquired on-board single 2-dimensional cine MRI. The method was evaluated using both digital extended-cardiac torso (XCAT) simulation of lung cancer patients and MRI data from 4 real liver cancer patients. The accuracy of the estimated VC-MRI was quantitatively evaluated using volume-percent-difference (VPD), center-of-mass-shift (COMS), and target tracking errors. Effects of acquisition orientation, region-of-interest (ROI) selection, patient breathing pattern change, and noise on the estimation accuracy were also evaluated. Results: Image subtraction of ground-truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground-truth with prior image. Agreement between normalized profiles in the estimated and ground-truth VC-MRI was achieved with less than 6% error for both XCAT and patient data. Among all XCAT scenarios, the VPD between ground-truth and estimated lesion volumes was, on average, 8.43 ± 1.52% and the COMS was, on average, 0.93 ± 0.58 mm across all time steps for estimation based on the ROI region in the sagittal cine images. Matching to ROI in the sagittal view achieved better accuracy when there was substantial breathing pattern change. The technique was robust against

A Technique for Generating Volumetric Cine-Magnetic Resonance Imaging

Energy Technology Data Exchange (ETDEWEB)

Harris, Wendy [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Ren, Lei, E-mail: lei.ren@duke.edu [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina (United States); Cai, Jing [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina (United States); Zhang, You [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Chang, Zheng; Yin, Fang-Fang [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina (United States)

2016-06-01

Purpose: The purpose of this study was to develop a techique to generate on-board volumetric cine-magnetic resonance imaging (VC-MRI) using patient prior images, motion modeling, and on-board 2-dimensional cine MRI. Methods and Materials: One phase of a 4-dimensional MRI acquired during patient simulation is used as patient prior images. Three major respiratory deformation patterns of the patient are extracted from 4-dimensional MRI based on principal-component analysis. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI. The deformation field is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by the data fidelity constraint using the acquired on-board single 2-dimensional cine MRI. The method was evaluated using both digital extended-cardiac torso (XCAT) simulation of lung cancer patients and MRI data from 4 real liver cancer patients. The accuracy of the estimated VC-MRI was quantitatively evaluated using volume-percent-difference (VPD), center-of-mass-shift (COMS), and target tracking errors. Effects of acquisition orientation, region-of-interest (ROI) selection, patient breathing pattern change, and noise on the estimation accuracy were also evaluated. Results: Image subtraction of ground-truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground-truth with prior image. Agreement between normalized profiles in the estimated and ground-truth VC-MRI was achieved with less than 6% error for both XCAT and patient data. Among all XCAT scenarios, the VPD between ground-truth and estimated lesion volumes was, on average, 8.43 ± 1.52% and the COMS was, on average, 0.93 ± 0.58 mm across all time steps for estimation based on the ROI region in the sagittal cine images. Matching to ROI in the sagittal view achieved better accuracy when there was substantial breathing pattern change. The technique was robust against

Volumetric velocimetry for fluid flows

Science.gov (United States)

Discetti, Stefano; Coletti, Filippo

2018-04-01

In recent years, several techniques have been introduced that are capable of extracting 3D three-component velocity fields in fluid flows. Fast-paced developments in both hardware and processing algorithms have generated a diverse set of methods, with a growing range of applications in flow diagnostics. This has been further enriched by the increasingly marked trend of hybridization, in which the differences between techniques are fading. In this review, we carry out a survey of the prominent methods, including optical techniques and approaches based on medical imaging. An overview of each is given with an example of an application from the literature, while focusing on their respective strengths and challenges. A framework for the evaluation of velocimetry performance in terms of dynamic spatial range is discussed, along with technological trends and emerging strategies to exploit 3D data. While critical challenges still exist, these observations highlight how volumetric techniques are transforming experimental fluid mechanics, and that the possibilities they offer have just begun to be explored.

Markerless registration for image guided surgery. Preoperative image, intraoperative video image, and patient

International Nuclear Information System (INIS)

Kihara, Tomohiko; Tanaka, Yuko

1998-01-01

Real-time and volumetric acquisition of X-ray CT, MR, and SPECT is the latest trend of the medical imaging devices. A clinical challenge is to use these multi-modality volumetric information complementary on patient in the entire diagnostic and surgical processes. The intraoperative image and patient integration intents to establish a common reference frame by image in diagnostic and surgical processes. This provides a quantitative measure during surgery, for which we have been relied mostly on doctors' skills and experiences. The intraoperative image and patient integration involves various technologies, however, we think one of the most important elements is the development of markerless registration, which should be efficient and applicable to the preoperative multi-modality data sets, intraoperative image, and patient. We developed a registration system which integrates preoperative multi-modality images, intraoperative video image, and patient. It consists of a real-time registration of video camera for intraoperative use, a markerless surface sampling matching of patient and image, our previous works of markerless multi-modality image registration of X-ray CT, MR, and SPECT, and an image synthesis on video image. We think these techniques can be used in many applications which involve video camera like devices such as video camera, microscope, and image Intensifier. (author)

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...

Efficient reconfigurable architectures for 3D medical image compression

OpenAIRE

Afandi, Ahmad

2010-01-01

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

Multimodality medical image database for temporal lobe epilepsy

Science.gov (United States)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Novel Volumetric Size and Velocity Measurement of Particles Using Interferometric Laser Imaging

Science.gov (United States)

Gunawardana, R.; Zarzecki, M.; Diez, F. J.

2008-11-01

Global Sizing Velocimetry (GSV) is a recently developed technique for characterizing the particle size distribution and flow velocity in a plane and in this research we extend this measurement to a volume through a laser scanning system. In GSV, a LASER sheet is used to illuminate translucent particles in a spray or flow field and the camera image is de-focused a known distance to create interference patterns. The diameters of the particles in the flow field are calculated by measuring the inter-fringe spacing in the resulting interferogram. Particle Imaging Velocimetry (PIV) techniques are used to compute velocity by measuring the particle displacement over a known short time interval. Researchers have recently begun applying GSV techniques to characterize sprays in a plane as it offers a larger area of investigation than other well known techniques such as Phase Doppler Anemometry (PDA). In this paper we extend GSA techniques from the current planar measurements to a volumetric measurement. The approach uses a high speed camera to acquire GSA images by scanning multiple planes in a volume of the flow field within a short period of time and obtain particle size distribution and velocity measurements in the entire volume.

An interactive, stereoscopic virtual environment for medical imaging visualization, simulation and training

Science.gov (United States)

Krueger, Evan; Messier, Erik; Linte, Cristian A.; Diaz, Gabriel

2017-03-01

Recent advances in medical image acquisition allow for the reconstruction of anatomies with 3D, 4D, and 5D renderings. Nevertheless, standard anatomical and medical data visualization still relies heavily on the use of traditional 2D didactic tools (i.e., textbooks and slides), which restrict the presentation of image data to a 2D slice format. While these approaches have their merits beyond being cost effective and easy to disseminate, anatomy is inherently three-dimensional. By using 2D visualizations to illustrate more complex morphologies, important interactions between structures can be missed. In practice, such as in the planning and execution of surgical interventions, professionals require intricate knowledge of anatomical complexities, which can be more clearly communicated and understood through intuitive interaction with 3D volumetric datasets, such as those extracted from high-resolution CT or MRI scans. Open source, high quality, 3D medical imaging datasets are freely available, and with the emerging popularity of 3D display technologies, affordable and consistent 3D anatomical visualizations can be created. In this study we describe the design, implementation, and evaluation of one such interactive, stereoscopic visualization paradigm for human anatomy extracted from 3D medical images. A stereoscopic display was created by projecting the scene onto the lab floor using sequential frame stereo projection and viewed through active shutter glasses. By incorporating a PhaseSpace motion tracking system, a single viewer can navigate an augmented reality environment and directly manipulate virtual objects in 3D. While this paradigm is sufficiently versatile to enable a wide variety of applications in need of 3D visualization, we designed our study to work as an interactive game, which allows users to explore the anatomy of various organs and systems. In this study we describe the design, implementation, and evaluation of an interactive and stereoscopic

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)

Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

Science.gov (United States)

Qiu, W; Titley-Peloquin, D; Soleimani, M

2012-11-01

Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

How 3D immersive visualization is changing medical diagnostics

Science.gov (United States)

Koning, Anton H. J.

2011-03-01

Originally the only way to look inside the human body without opening it up was by means of two dimensional (2D) images obtained using X-ray equipment. The fact that human anatomy is inherently three dimensional leads to ambiguities in interpretation and problems of occlusion. Three dimensional (3D) imaging modalities such as CT, MRI and 3D ultrasound remove these drawbacks and are now part of routine medical care. While most hospitals 'have gone digital', meaning that the images are no longer printed on film, they are still being viewed on 2D screens. However, this way valuable depth information is lost, and some interactions become unnecessarily complex or even unfeasible. Using a virtual reality (VR) system to present volumetric data means that depth information is presented to the viewer and 3D interaction is made possible. At the Erasmus MC we have developed V-Scope, an immersive volume visualization system for visualizing a variety of (bio-)medical volumetric datasets, ranging from 3D ultrasound, via CT and MRI, to confocal microscopy, OPT and 3D electron-microscopy data. In this talk we will address the advantages of such a system for both medical diagnostics as well as for (bio)medical research.

SU-E-I-10: Investigation On Detectability of a Small Target for Different Slice Direction of a Volumetric Cone Beam CT Image

Energy Technology Data Exchange (ETDEWEB)

Lee, C; Han, M; Baek, J [Yonsei University, Incheon (Korea, Republic of)

2015-06-15

Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR{sup 2} ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201

SU-E-I-10: Investigation On Detectability of a Small Target for Different Slice Direction of a Volumetric Cone Beam CT Image

International Nuclear Information System (INIS)

Lee, C; Han, M; Baek, J

2015-01-01

Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR 2 ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201

Area and volumetric density estimation in processed full-field digital mammograms for risk assessment of breast cancer.

Directory of Open Access Journals (Sweden)

Abbas Cheddad

Full Text Available INTRODUCTION: Mammographic density, the white radiolucent part of a mammogram, is a marker of breast cancer risk and mammographic sensitivity. There are several means of measuring mammographic density, among which are area-based and volumetric-based approaches. Current volumetric methods use only unprocessed, raw mammograms, which is a problematic restriction since such raw mammograms are normally not stored. We describe fully automated methods for measuring both area and volumetric mammographic density from processed images. METHODS: The data set used in this study comprises raw and processed images of the same view from 1462 women. We developed two algorithms for processed images, an automated area-based approach (CASAM-Area and a volumetric-based approach (CASAM-Vol. The latter method was based on training a random forest prediction model with image statistical features as predictors, against a volumetric measure, Volpara, for corresponding raw images. We contrast the three methods, CASAM-Area, CASAM-Vol and Volpara directly and in terms of association with breast cancer risk and a known genetic variant for mammographic density and breast cancer, rs10995190 in the gene ZNF365. Associations with breast cancer risk were evaluated using images from 47 breast cancer cases and 1011 control subjects. The genetic association analysis was based on 1011 control subjects. RESULTS: All three measures of mammographic density were associated with breast cancer risk and rs10995190 (p0.10 for risk, p>0.03 for rs10995190. CONCLUSIONS: Our results show that it is possible to obtain reliable automated measures of volumetric and area mammographic density from processed digital images. Area and volumetric measures of density on processed digital images performed similar in terms of risk and genetic association.

Spatial and volumetric changes of retroperitoneal sarcomas during pre-operative radiotherapy

International Nuclear Information System (INIS)

Wong, Philip; Dickie, Colleen; Lee, David; Chung, Peter; O’Sullivan, Brian; Letourneau, Daniel; Xu, Wei; Swallow, Carol; Gladdy, Rebecca; Catton, Charles

2014-01-01

Purpose: To determine the positional and volumetric changes of retroperitoneal sarcomas (RPS) during pre-operative external beam radiotherapy (PreRT). Material and methods: After excluding 2 patients who received chemotherapy prior to PreRT and 15 RPS that were larger than the field-of-view of cone-beam CT (CBCT), the positional and volumetric changes of RPS throughout PreRT were characterized in 19 patients treated with IMRT using CBCT image guidance. Analysis was performed on 118 CBCT images representing one image per week of those acquired daily during treatment. Intra-fraction breathing motions of the gross tumor volume (GTV) and kidneys were measured in 22 RPS patients simulated using 4D-CT. Fifteen other patients were excluded whose tumors were incompletely imaged on CBCT or who received pre-RT chemotherapy. Results: A GTV volumetric increase (mean: 6.6%, p = 0.035) during the first 2 weeks (CBCT1 vs. CBCT2) of treatment was followed by GTV volumetric decrease (mean: 4%, p = 0.009) by completion of radiotherapy (CBCT1 vs. CBCT6). Internal margins of 8.6, 15 and 15 mm in the lateral, anterior/posterior and superior/inferior directions would be required to account for inter-fraction displacements. The extent of GTV respiratory motion was significantly (p < 0.0001) correlated with more superiorly positioned tumors. Conclusion: Inter-fraction CBCT provides important volumetric and positional information of RPS which may improve PreRT quality and prompt re-planning. Planning target volume may be reduced using online soft-tissue matching to account for interfractional displacements of GTVs. Important breathing motion occurred in superiorly placed RPS supporting the utility of 4D-CT planning

Volumetric Arterial Wall Shear Stress Calculation Based on Cine Phase Contrast MRI

NARCIS (Netherlands)

Potters, Wouter V.; van Ooij, Pim; Marquering, Henk; VanBavel, Ed; Nederveen, Aart J.

2015-01-01

PurposeTo assess the accuracy and precision of a volumetric wall shear stress (WSS) calculation method applied to cine phase contrast magnetic resonance imaging (PC-MRI) data. Materials and MethodsVolumetric WSS vectors were calculated in software phantoms. WSS algorithm parameters were optimized

MR volumetric assessment of endolymphatic hydrops

International Nuclear Information System (INIS)

Guerkov, R.; Berman, A.; Jerin, C.; Krause, E.; Dietrich, O.; Flatz, W.; Ertl-Wagner, B.; Keeser, D.

2015-01-01

We aimed to volumetrically quantify endolymph and perilymph spaces of the inner ear in order to establish a methodological basis for further investigations into the pathophysiology and therapeutic monitoring of Meniere's disease. Sixteen patients (eight females, aged 38-71 years) with definite unilateral Meniere's disease were included in this study. Magnetic resonance (MR) cisternography with a T2-SPACE sequence was combined with a Real reconstruction inversion recovery (Real-IR) sequence for delineation of inner ear fluid spaces. Machine learning and automated local thresholding segmentation algorithms were applied for three-dimensional (3D) reconstruction and volumetric quantification of endolymphatic hydrops. Test-retest reliability was assessed by the intra-class coefficient; correlation of cochlear endolymph volume ratio with hearing function was assessed by the Pearson correlation coefficient. Endolymph volume ratios could be reliably measured in all patients, with a mean (range) value of 15 % (2-25) for the cochlea and 28 % (12-40) for the vestibulum. Test-retest reliability was excellent, with an intra-class coefficient of 0.99. Cochlear endolymphatic hydrops was significantly correlated with hearing loss (r = 0.747, p = 0.001). MR imaging after local contrast application and image processing, including machine learning and automated local thresholding, enable the volumetric quantification of endolymphatic hydrops. This allows for a quantitative assessment of the effect of therapeutic interventions on endolymphatic hydrops. (orig.)

MR volumetric assessment of endolymphatic hydrops

Energy Technology Data Exchange (ETDEWEB)

Guerkov, R.; Berman, A.; Jerin, C.; Krause, E. [University of Munich, Department of Otorhinolaryngology Head and Neck Surgery, Grosshadern Medical Centre, Munich (Germany); University of Munich, German Centre for Vertigo and Balance Disorders, Grosshadern Medical Centre, Marchioninistr. 15, 81377, Munich (Germany); Dietrich, O.; Flatz, W.; Ertl-Wagner, B. [University of Munich, Institute of Clinical Radiology, Grosshadern Medical Centre, Munich (Germany); Keeser, D. [University of Munich, Institute of Clinical Radiology, Grosshadern Medical Centre, Munich (Germany); University of Munich, German Centre for Vertigo and Balance Disorders, Grosshadern Medical Centre, Marchioninistr. 15, 81377, Munich (Germany); University of Munich, Department of Psychiatry and Psychotherapy, Innenstadtkliniken Medical Centre, Munich (Germany)

2014-10-16

We aimed to volumetrically quantify endolymph and perilymph spaces of the inner ear in order to establish a methodological basis for further investigations into the pathophysiology and therapeutic monitoring of Meniere's disease. Sixteen patients (eight females, aged 38-71 years) with definite unilateral Meniere's disease were included in this study. Magnetic resonance (MR) cisternography with a T2-SPACE sequence was combined with a Real reconstruction inversion recovery (Real-IR) sequence for delineation of inner ear fluid spaces. Machine learning and automated local thresholding segmentation algorithms were applied for three-dimensional (3D) reconstruction and volumetric quantification of endolymphatic hydrops. Test-retest reliability was assessed by the intra-class coefficient; correlation of cochlear endolymph volume ratio with hearing function was assessed by the Pearson correlation coefficient. Endolymph volume ratios could be reliably measured in all patients, with a mean (range) value of 15 % (2-25) for the cochlea and 28 % (12-40) for the vestibulum. Test-retest reliability was excellent, with an intra-class coefficient of 0.99. Cochlear endolymphatic hydrops was significantly correlated with hearing loss (r = 0.747, p = 0.001). MR imaging after local contrast application and image processing, including machine learning and automated local thresholding, enable the volumetric quantification of endolymphatic hydrops. This allows for a quantitative assessment of the effect of therapeutic interventions on endolymphatic hydrops. (orig.)

Volumetric, dashboard-mounted augmented display

Science.gov (United States)

Kessler, David; Grabowski, Christopher

2017-11-01

The optical design of a compact volumetric display for drivers is presented. The system displays a true volume image with realistic physical depth cues, such as focal accommodation, parallax and convergence. A large eyebox is achieved with a pupil expander. The windshield is used as the augmented reality combiner. A freeform windshield corrector is placed at the dashboard.

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

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.

Somatic mutations associated with MRI-derived volumetric features in glioblastoma

Energy Technology Data Exchange (ETDEWEB)

Gutman, David A.; Dunn, William D. [Emory University School of Medicine, Departments of Neurology, Atlanta, GA (United States); Emory University School of Medicine, Biomedical Informatics, Atlanta, GA (United States); Grossmann, Patrick; Alexander, Brian M. [Harvard Medical School, Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women' s Hospital, Boston, MA (United States); Cooper, Lee A.D. [Emory University School of Medicine, Biomedical Informatics, Atlanta, GA (United States); Georgia Institute of Technology, Department of Biomedical Engineering, Atlanta, GA (United States); Holder, Chad A. [Emory University School of Medicine, Radiology and Imaging Sciences, Atlanta, GA (United States); Ligon, Keith L. [Brigham and Women' s Hospital, Harvard Medical School, Pathology, Dana-Farber Cancer Institute, Boston, MA (United States); Aerts, Hugo J.W.L. [Harvard Medical School, Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women' s Hospital, Boston, MA (United States); Brigham and Women' s Hospital, Harvard Medical School, Radiology, Dana-Farber Cancer Institute, Boston, MA (United States)

2015-12-15

MR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM). Seventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status. Our results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature. MRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine. (orig.)

Somatic mutations associated with MRI-derived volumetric features in glioblastoma

International Nuclear Information System (INIS)

Gutman, David A.; Dunn, William D.; Grossmann, Patrick; Alexander, Brian M.; Cooper, Lee A.D.; Holder, Chad A.; Ligon, Keith L.; Aerts, Hugo J.W.L.

2015-01-01

MR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM). Seventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status. Our results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature. MRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine. (orig.)

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.)

Sub-diffraction limit localization of proteins in volumetric space using Bayesian restoration of fluorescence images from ultrathin specimens.

Directory of Open Access Journals (Sweden)

Gordon Wang

Full Text Available Photon diffraction limits the resolution of conventional light microscopy at the lateral focal plane to 0.61λ/NA (λ = wavelength of light, NA = numerical aperture of the objective and at the axial plane to 1.4nλ/NA(2 (n = refractive index of the imaging medium, 1.51 for oil immersion, which with visible wavelengths and a 1.4NA oil immersion objective is -220 nm and -600 nm in the lateral plane and axial plane respectively. This volumetric resolution is too large for the proper localization of protein clustering in subcellular structures. Here we combine the newly developed proteomic imaging technique, Array Tomography (AT, with its native 50-100 nm axial resolution achieved by physical sectioning of resin embedded tissue, and a 2D maximum likelihood deconvolution method, based on Bayes' rule, which significantly improves the resolution of protein puncta in the lateral plane to allow accurate and fast computational segmentation and analysis of labeled proteins. The physical sectioning of AT allows tissue specimens to be imaged at the physical optimum of modern high NA plan-apochormatic objectives. This translates to images that have little out of focus light, minimal aberrations and wave-front distortions. Thus, AT is able to provide images with truly invariant point spread functions (PSF, a property critical for accurate deconvolution. We show that AT with deconvolution increases the volumetric analytical fidelity of protein localization by significantly improving the modulation of high spatial frequencies up to and potentially beyond the spatial frequency cut-off of the objective. Moreover, we are able to achieve this improvement with no noticeable introduction of noise or artifacts and arrive at object segmentation and localization accuracies on par with image volumes captured using commercial implementations of super-resolution microscopes.

Eye-tracking of nodule detection in lung CT volumetric data

Energy Technology Data Exchange (ETDEWEB)

Diaz, Ivan; Verdun, Francis R.; Bochud, François O., E-mail: francois.bochud@chuv.ch [Institute of Radiation Physics, Lausanne University Hospital, Lausanne 1004 (Switzerland); Schmidt, Sabine [Department of Radiology, Lausanne University Hospital, Lausanne 1004 (Switzerland)

2015-06-15

Purpose: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naïve observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll through image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. Methods: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naïve observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. Results: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naïve observers and the radiologists at the moment the signal

Toward public volume database management: a case study of NOVA, the National Online Volumetric Archive

Science.gov (United States)

Fletcher, Alex; Yoo, Terry S.

2004-04-01

Public databases today can be constructed with a wide variety of authoring and management structures. The widespread appeal of Internet search engines suggests that public information be made open and available to common search strategies, making accessible information that would otherwise be hidden by the infrastructure and software interfaces of a traditional database management system. We present the construction and organizational details for managing NOVA, the National Online Volumetric Archive. As an archival effort of the Visible Human Project for supporting medical visualization research, archiving 3D multimodal radiological teaching files, and enhancing medical education with volumetric data, our overall database structure is simplified; archives grow by accruing information, but seldom have to modify, delete, or overwrite stored records. NOVA is being constructed and populated so that it is transparent to the Internet; that is, much of its internal structure is mirrored in HTML allowing internet search engines to investigate, catalog, and link directly to the deep relational structure of the collection index. The key organizational concept for NOVA is the Image Content Group (ICG), an indexing strategy for cataloging incoming data as a set structure rather than by keyword management. These groups are managed through a series of XML files and authoring scripts. We cover the motivation for Image Content Groups, their overall construction, authorship, and management in XML, and the pilot results for creating public data repositories using this strategy.

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

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

A novel 3D volumetric voxel registration technique for volume-view-guided image registration of multiple imaging modalities

International Nuclear Information System (INIS)

Li Guang; Xie Huchen; Ning, Holly; Capala, Jacek; Arora, Barbara C.; Coleman, C. Norman; Camphausen, Kevin; Miller, Robert W.

2005-01-01

Purpose: To provide more clinically useful image registration with improved accuracy and reduced time, a novel technique of three-dimensional (3D) volumetric voxel registration of multimodality images is developed. Methods and Materials: This technique can register up to four concurrent images from multimodalities with volume view guidance. Various visualization effects can be applied, facilitating global and internal voxel registration. Fourteen computed tomography/magnetic resonance (CT/MR) image sets and two computed tomography/positron emission tomography (CT/PET) image sets are used. For comparison, an automatic registration technique using maximization of mutual information (MMI) and a three-orthogonal-planar (3P) registration technique are used. Results: Visually sensitive registration criteria for CT/MR and CT/PET have been established, including the homogeneity of color distribution. Based on the registration results of 14 CT/MR images, the 3D voxel technique is in excellent agreement with the automatic MMI technique and is indicatory of a global positioning error (defined as the means and standard deviations of the error distribution) using the 3P pixel technique: 1.8 deg ± 1.2 deg in rotation and 2.0 ± 1.3 (voxel unit) in translation. To the best of our knowledge, this is the first time that such positioning error has been addressed. Conclusion: This novel 3D voxel technique establishes volume-view-guided image registration of up to four modalities. It improves registration accuracy with reduced time, compared with the 3P pixel technique. This article suggests that any interactive and automatic registration should be safeguarded using the 3D voxel technique

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

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.

Coaxial volumetric velocimetry

Science.gov (United States)

Schneiders, Jan F. G.; Scarano, Fulvio; Jux, Constantin; Sciacchitano, Andrea

2018-06-01

This study describes the working principles of the coaxial volumetric velocimeter (CVV) for wind tunnel measurements. The measurement system is derived from the concept of tomographic PIV in combination with recent developments of Lagrangian particle tracking. The main characteristic of the CVV is its small tomographic aperture and the coaxial arrangement between the illumination and imaging directions. The system consists of a multi-camera arrangement subtending only few degrees solid angle and a long focal depth. Contrary to established PIV practice, laser illumination is provided along the same direction as that of the camera views, reducing the optical access requirements to a single viewing direction. The laser light is expanded to illuminate the full field of view of the cameras. Such illumination and imaging conditions along a deep measurement volume dictate the use of tracer particles with a large scattering area. In the present work, helium-filled soap bubbles are used. The fundamental principles of the CVV in terms of dynamic velocity and spatial range are discussed. Maximum particle image density is shown to limit tracer particle seeding concentration and instantaneous spatial resolution. Time-averaged flow fields can be obtained at high spatial resolution by ensemble averaging. The use of the CVV for time-averaged measurements is demonstrated in two wind tunnel experiments. After comparing the CVV measurements with the potential flow in front of a sphere, the near-surface flow around a complex wind tunnel model of a cyclist is measured. The measurements yield the volumetric time-averaged velocity and vorticity field. The measurements of the streamlines in proximity of the surface give an indication of the skin-friction lines pattern, which is of use in the interpretation of the surface flow topology.

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.)

Volumetric 3D Display System with Static Screen

Science.gov (United States)

Geng, Jason

2011-01-01

Current display technology has relied on flat, 2D screens that cannot truly convey the third dimension of visual information: depth. In contrast to conventional visualization that is primarily based on 2D flat screens, the volumetric 3D display possesses a true 3D display volume, and places physically each 3D voxel in displayed 3D images at the true 3D (x,y,z) spatial position. Each voxel, analogous to a pixel in a 2D image, emits light from that position to form a real 3D image in the eyes of the viewers. Such true volumetric 3D display technology provides both physiological (accommodation, convergence, binocular disparity, and motion parallax) and psychological (image size, linear perspective, shading, brightness, etc.) depth cues to human visual systems to help in the perception of 3D objects. In a volumetric 3D display, viewers can watch the displayed 3D images from a completely 360 view without using any special eyewear. The volumetric 3D display techniques may lead to a quantum leap in information display technology and can dramatically change the ways humans interact with computers, which can lead to significant improvements in the efficiency of learning and knowledge management processes. Within a block of glass, a large amount of tiny dots of voxels are created by using a recently available machining technique called laser subsurface engraving (LSE). The LSE is able to produce tiny physical crack points (as small as 0.05 mm in diameter) at any (x,y,z) location within the cube of transparent material. The crack dots, when illuminated by a light source, scatter the light around and form visible voxels within the 3D volume. The locations of these tiny voxels are strategically determined such that each can be illuminated by a light ray from a high-resolution digital mirror device (DMD) light engine. The distribution of these voxels occupies the full display volume within the static 3D glass screen. This design eliminates any moving screen seen in previous

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.

Design, Implementation and Characterization of a Quantum-Dot-Based Volumetric Display

Science.gov (United States)

Hirayama, Ryuji; Naruse, Makoto; Nakayama, Hirotaka; Tate, Naoya; Shiraki, Atsushi; Kakue, Takashi; Shimobaba, Tomoyoshi; Ohtsu, Motoichi; Ito, Tomoyoshi

2015-02-01

In this study, we propose and experimentally demonstrate a volumetric display system based on quantum dots (QDs) embedded in a polymer substrate. Unlike conventional volumetric displays, our system does not require electrical wiring; thus, the heretofore unavoidable issue of occlusion is resolved because irradiation by external light supplies the energy to the light-emitting voxels formed by the QDs. By exploiting the intrinsic attributes of the QDs, the system offers ultrahigh definition and a wide range of colours for volumetric displays. In this paper, we discuss the design, implementation and characterization of the proposed volumetric display's first prototype. We developed an 8 × 8 × 8 display comprising two types of QDs. This display provides multicolour three-type two-dimensional patterns when viewed from different angles. The QD-based volumetric display provides a new way to represent images and could be applied in leisure and advertising industries, among others.

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.)

[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...

Low-cost Volumetric Ultrasound by Augmentation of 2D Systems: Design and Prototype.

Science.gov (United States)

Herickhoff, Carl D; Morgan, Matthew R; Broder, Joshua S; Dahl, Jeremy J

2018-01-01

Conventional two-dimensional (2D) ultrasound imaging is a powerful diagnostic tool in the hands of an experienced user, yet 2D ultrasound remains clinically underutilized and inherently incomplete, with output being very operator dependent. Volumetric ultrasound systems can more fully capture a three-dimensional (3D) region of interest, but current 3D systems require specialized transducers, are prohibitively expensive for many clinical departments, and do not register image orientation with respect to the patient; these systems are designed to provide improved workflow rather than operator independence. This work investigates whether it is possible to add volumetric 3D imaging capability to existing 2D ultrasound systems at minimal cost, providing a practical means of reducing operator dependence in ultrasound. In this paper, we present a low-cost method to make 2D ultrasound systems capable of quality volumetric image acquisition: we present the general system design and image acquisition method, including the use of a probe-mounted orientation sensor, a simple probe fixture prototype, and an offline volume reconstruction technique. We demonstrate initial results of the method, implemented using a Verasonics Vantage research scanner.

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.

MO-DE-210-06: Development of a Supercompounded 3D Volumetric Ultrasound Image Guidance System for Prone Accelerated Partial Breast Irradiation (APBI)

Energy Technology Data Exchange (ETDEWEB)

Chiu, T; Hrycushko, B; Zhao, B; Jiang, S; Gu, X [UT Southwestern Medical Center, Dallas, TX (United States)

2015-06-15

Purpose: For early-stage breast cancer, accelerated partial breast irradiation (APBI) is a cost-effective breast-conserving treatment. Irradiation in a prone position can mitigate respiratory induced breast movement and achieve maximal sparing of heart and lung tissues. However, accurate dose delivery is challenging due to breast deformation and lumpectomy cavity shrinkage. We propose a 3D volumetric ultrasound (US) image guidance system for accurate prone APBI Methods: The designed system, set beneath the prone breast board, consists of a water container, an US scanner, and a two-layer breast immobilization cup. The outer layer of the breast cup forms the inner wall of water container while the inner layer is attached to patient breast directly to immobilization. The US transducer scans is attached to the outer-layer of breast cup at the dent of water container. Rotational US scans in a transverse plane are achieved by simultaneously rotating water container and transducer, and multiple transverse scanning forms a 3D scan. A supercompounding-technique-based volumetric US reconstruction algorithm is developed for 3D image reconstruction. The performance of the designed system is evaluated with two custom-made gelatin phantoms containing several cylindrical inserts filled in with water (11% reflection coefficient between materials). One phantom is designed for positioning evaluation while the other is for scaling assessment. Results: In the positioning evaluation phantom, the central distances between the inserts are 15, 20, 30 and 40 mm. The distances on reconstructed images differ by −0.19, −0.65, −0.11 and −1.67 mm, respectively. In the scaling evaluation phantom, inserts are 12.7, 19.05, 25.40 and 31.75 mm in diameter. Measured inserts’ sizes on images differed by 0.23, 0.19, −0.1 and 0.22 mm, respectively. Conclusion: The phantom evaluation results show that the developed 3D volumetric US system can accurately localize target position and determine

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

Mobile medical image retrieval

Science.gov (United States)

Duc, Samuel; Depeursinge, Adrien; Eggel, Ivan; Müller, Henning

2011-03-01

Images are an integral part of medical practice for diagnosis, treatment planning and teaching. Image retrieval has gained in importance mainly as a research domain over the past 20 years. Both textual and visual retrieval of images are essential. In the process of mobile devices becoming reliable and having a functionality equaling that of formerly desktop clients, mobile computing has gained ground and many applications have been explored. This creates a new field of mobile information search & access and in this context images can play an important role as they often allow understanding complex scenarios much quicker and easier than free text. Mobile information retrieval in general has skyrocketed over the past year with many new applications and tools being developed and all sorts of interfaces being adapted to mobile clients. This article describes constraints of an information retrieval system including visual and textual information retrieval from the medical literature of BioMedCentral and of the RSNA journals Radiology and Radiographics. Solutions for mobile data access with an example on an iPhone in a web-based environment are presented as iPhones are frequently used and the operating system is bound to become the most frequent smartphone operating system in 2011. A web-based scenario was chosen to allow for a use by other smart phone platforms such as Android as well. Constraints of small screens and navigation with touch screens are taken into account in the development of the application. A hybrid choice had to be taken to allow for taking pictures with the cell phone camera and upload them for visual similarity search as most producers of smart phones block this functionality to web applications. Mobile information access and in particular access to images can be surprisingly efficient and effective on smaller screens. Images can be read on screen much faster and relevance of documents can be identified quickly through the use of images contained in

Influence of Cobb Angle and ISIS2 Surface Topography Volumetric Asymmetry on Scoliosis Research Society-22 Outcome Scores in Scoliosis.

Science.gov (United States)

Brewer, Paul; Berryman, Fiona; Baker, De; Pynsent, Paul; Gardner, Adrian

2013-11-01

Retrospective sequential patient series. To establish the relationship between the magnitude of the deformity in scoliosis and patients' perception of their condition, as measured with Scoliosis Research Society-22 scores. A total of 93 untreated patients with adolescent idiopathic scoliosis were included retrospectively. The Cobb angle was measured from a plain radiograph, and volumetric asymmetry was measured by ISIS2 surface topography. The association between Scoliosis Research Society scores for function, pain, self-image, and mental health against Cobb angle and volumetric asymmetry was investigated using the Pearson correlation coefficient. Correlation of both Cobb angle and volumetric asymmetry with function and pain was weak (all self-image, was higher, although still moderate (-.37 for Cobb angle and -.44 for volumetric asymmetry). Both were statistically significant (Cobb angle, p = .0002; volumetric asymmetry; p = .00001). Cobb angle contributed 13.8% to the linear relationship with self-image, whereas volumetric asymmetry contributed 19.3%. For mental health, correlation was statistically significant with Cobb angle (p = .011) and volumetric asymmetry (p = .0005), but the correlation was low to moderate (-.26 and -.35, respectively). Cobb angle contributed 6.9% to the linear relationship with mental health, whereas volumetric asymmetry contributed 12.4%. Volumetric asymmetry correlates better with both mental health and self-image compared with Cobb angle, but the correlation was only moderate. This study suggests that a patient's own perception of self-image and mental health is multifactorial and not completely explained through present objective measurements of the size of the deformity. This helps to explain the difficulties in any objective analysis of a problem with multifactorial perception issues. Further study is required to investigate other physical aspects of the deformity that may have a role in how patients view themselves. Copyright �

Post-processing methods of rendering and visualizing 3-D reconstructed tomographic images

Energy Technology Data Exchange (ETDEWEB)

Wong, S.T.C. [Univ. of California, San Francisco, CA (United States)

1997-02-01

The purpose of this presentation is to discuss the computer processing techniques of tomographic images, after they have been generated by imaging scanners, for volume visualization. Volume visualization is concerned with the representation, manipulation, and rendering of volumetric data. Since the first digital images were produced from computed tomography (CT) scanners in the mid 1970s, applications of visualization in medicine have expanded dramatically. Today, three-dimensional (3D) medical visualization has expanded from using CT data, the first inherently digital source of 3D medical data, to using data from various medical imaging modalities, including magnetic resonance scanners, positron emission scanners, digital ultrasound, electronic and confocal microscopy, and other medical imaging modalities. We have advanced from rendering anatomy to aid diagnosis and visualize complex anatomic structures to planning and assisting surgery and radiation treatment. New, more accurate and cost-effective procedures for clinical services and biomedical research have become possible by integrating computer graphics technology with medical images. This trend is particularly noticeable in current market-driven health care environment. For example, interventional imaging, image-guided surgery, and stereotactic and visualization techniques are now stemming into surgical practice. In this presentation, we discuss only computer-display-based approaches of volumetric medical visualization. That is, we assume that the display device available is two-dimensional (2D) in nature and all analysis of multidimensional image data is to be carried out via the 2D screen of the device. There are technologies such as holography and virtual reality that do provide a {open_quotes}true 3D screen{close_quotes}. To confine the scope, this presentation will not discuss such approaches.

Post-processing methods of rendering and visualizing 3-D reconstructed tomographic images

International Nuclear Information System (INIS)

Wong, S.T.C.

1997-01-01

The purpose of this presentation is to discuss the computer processing techniques of tomographic images, after they have been generated by imaging scanners, for volume visualization. Volume visualization is concerned with the representation, manipulation, and rendering of volumetric data. Since the first digital images were produced from computed tomography (CT) scanners in the mid 1970s, applications of visualization in medicine have expanded dramatically. Today, three-dimensional (3D) medical visualization has expanded from using CT data, the first inherently digital source of 3D medical data, to using data from various medical imaging modalities, including magnetic resonance scanners, positron emission scanners, digital ultrasound, electronic and confocal microscopy, and other medical imaging modalities. We have advanced from rendering anatomy to aid diagnosis and visualize complex anatomic structures to planning and assisting surgery and radiation treatment. New, more accurate and cost-effective procedures for clinical services and biomedical research have become possible by integrating computer graphics technology with medical images. This trend is particularly noticeable in current market-driven health care environment. For example, interventional imaging, image-guided surgery, and stereotactic and visualization techniques are now stemming into surgical practice. In this presentation, we discuss only computer-display-based approaches of volumetric medical visualization. That is, we assume that the display device available is two-dimensional (2D) in nature and all analysis of multidimensional image data is to be carried out via the 2D screen of the device. There are technologies such as holography and virtual reality that do provide a open-quotes true 3D screenclose quotes. To confine the scope, this presentation will not discuss such approaches

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...

Volumetric velocity measurements in restricted geometries using spiral sampling: a phantom study.

Science.gov (United States)

Nilsson, Anders; Revstedt, Johan; Heiberg, Einar; Ståhlberg, Freddy; Bloch, Karin Markenroth

2015-04-01

The aim of this study was to evaluate the accuracy of maximum velocity measurements using volumetric phase-contrast imaging with spiral readouts in a stenotic flow phantom. In a phantom model, maximum velocity, flow, pressure gradient, and streamline visualizations were evaluated using volumetric phase-contrast magnetic resonance imaging (MRI) with velocity encoding in one (extending on current clinical practice) and three directions (for characterization of the flow field) using spiral readouts. Results of maximum velocity and pressure drop were compared to computational fluid dynamics (CFD) simulations, as well as corresponding low-echo-time (TE) Cartesian data. Flow was compared to 2D through-plane phase contrast (PC) upstream from the restriction. Results obtained with 3D through-plane PC as well as 4D PC at shortest TE using a spiral readout showed excellent agreements with the maximum velocity values obtained with CFD (spiral sequences were respectively 14 and 13 % overestimated compared to CFD. Identification of the maximum velocity location, as well as the accurate velocity quantification can be obtained in stenotic regions using short-TE spiral volumetric PC imaging.

Extended Kalman filtering for continuous volumetric MR-temperature imaging.

Science.gov (United States)

Denis de Senneville, Baudouin; Roujol, Sébastien; Hey, Silke; Moonen, Chrit; Ries, Mario

2013-04-01

Real time magnetic resonance (MR) thermometry has evolved into the method of choice for the guidance of high-intensity focused ultrasound (HIFU) interventions. For this role, MR-thermometry should preferably have a high temporal and spatial resolution and allow observing the temperature over the entire targeted area and its vicinity with a high accuracy. In addition, the precision of real time MR-thermometry for therapy guidance is generally limited by the available signal-to-noise ratio (SNR) and the influence of physiological noise. MR-guided HIFU would benefit of the large coverage volumetric temperature maps, including characterization of volumetric heating trajectories as well as near- and far-field heating. In this paper, continuous volumetric MR-temperature monitoring was obtained as follows. The targeted area was continuously scanned during the heating process by a multi-slice sequence. Measured data and a priori knowledge of 3-D data derived from a forecast based on a physical model were combined using an extended Kalman filter (EKF). The proposed reconstruction improved the temperature measurement resolution and precision while maintaining guaranteed output accuracy. The method was evaluated experimentally ex vivo on a phantom, and in vivo on a porcine kidney, using HIFU heating. On the in vivo experiment, it allowed the reconstruction from a spatio-temporally under-sampled data set (with an update rate for each voxel of 1.143 s) to a 3-D dataset covering a field of view of 142.5×285×54 mm(3) with a voxel size of 3×3×6 mm(3) and a temporal resolution of 0.127 s. The method also provided noise reduction, while having a minimal impact on accuracy and latency.

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.)

Agreement of mammographic measures of volumetric breast density to MRI.

Directory of Open Access Journals (Sweden)

Jeff Wang

Full Text Available Clinical scores of mammographic breast density are highly subjective. Automated technologies for mammography exist to quantify breast density objectively, but the technique that most accurately measures the quantity of breast fibroglandular tissue is not known.To compare the agreement of three automated mammographic techniques for measuring volumetric breast density with a quantitative volumetric MRI-based technique in a screening population.Women were selected from the UCSF Medical Center screening population that had received both a screening MRI and digital mammogram within one year of each other, had Breast Imaging Reporting and Data System (BI-RADS assessments of normal or benign finding, and no history of breast cancer or surgery. Agreement was assessed of three mammographic techniques (Single-energy X-ray Absorptiometry [SXA], Quantra, and Volpara with MRI for percent fibroglandular tissue volume, absolute fibroglandular tissue volume, and total breast volume.Among 99 women, the automated mammographic density techniques were correlated with MRI measures with R(2 values ranging from 0.40 (log fibroglandular volume to 0.91 (total breast volume. Substantial agreement measured by kappa statistic was found between all percent fibroglandular tissue measures (0.72 to 0.63, but only moderate agreement for log fibroglandular volumes. The kappa statistics for all percent density measures were highest in the comparisons of the SXA and MRI results. The largest error source between MRI and the mammography techniques was found to be differences in measures of total breast volume.Automated volumetric fibroglandular tissue measures from screening digital mammograms were in substantial agreement with MRI and if associated with breast cancer could be used in clinical practice to enhance risk assessment and prevention.

Agreement of mammographic measures of volumetric breast density to MRI.

Science.gov (United States)

Wang, Jeff; Azziz, Ania; Fan, Bo; Malkov, Serghei; Klifa, Catherine; Newitt, David; Yitta, Silaja; Hylton, Nola; Kerlikowske, Karla; Shepherd, John A

2013-01-01

Clinical scores of mammographic breast density are highly subjective. Automated technologies for mammography exist to quantify breast density objectively, but the technique that most accurately measures the quantity of breast fibroglandular tissue is not known. To compare the agreement of three automated mammographic techniques for measuring volumetric breast density with a quantitative volumetric MRI-based technique in a screening population. Women were selected from the UCSF Medical Center screening population that had received both a screening MRI and digital mammogram within one year of each other, had Breast Imaging Reporting and Data System (BI-RADS) assessments of normal or benign finding, and no history of breast cancer or surgery. Agreement was assessed of three mammographic techniques (Single-energy X-ray Absorptiometry [SXA], Quantra, and Volpara) with MRI for percent fibroglandular tissue volume, absolute fibroglandular tissue volume, and total breast volume. Among 99 women, the automated mammographic density techniques were correlated with MRI measures with R(2) values ranging from 0.40 (log fibroglandular volume) to 0.91 (total breast volume). Substantial agreement measured by kappa statistic was found between all percent fibroglandular tissue measures (0.72 to 0.63), but only moderate agreement for log fibroglandular volumes. The kappa statistics for all percent density measures were highest in the comparisons of the SXA and MRI results. The largest error source between MRI and the mammography techniques was found to be differences in measures of total breast volume. Automated volumetric fibroglandular tissue measures from screening digital mammograms were in substantial agreement with MRI and if associated with breast cancer could be used in clinical practice to enhance risk assessment and prevention.

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...

Integration and evaluation of a needle-positioning robot with volumetric microcomputed tomography image guidance for small animal stereotactic interventions

International Nuclear Information System (INIS)

Waspe, Adam C.; McErlain, David D.; Pitelka, Vasek; Holdsworth, David W.; Lacefield, James C.; Fenster, Aaron

2010-01-01

Purpose: Preclinical research protocols often require insertion of needles to specific targets within small animal brains. To target biologically relevant locations in rodent brains more effectively, a robotic device has been developed that is capable of positioning a needle along oblique trajectories through a single burr hole in the skull under volumetric microcomputed tomography (micro-CT) guidance. Methods: An x-ray compatible stereotactic frame secures the head throughout the procedure using a bite bar, nose clamp, and ear bars. CT-to-robot registration enables structures identified in the image to be mapped to physical coordinates in the brain. Registration is accomplished by injecting a barium sulfate contrast agent as the robot withdraws the needle from predefined points in a phantom. Registration accuracy is affected by the robot-positioning error and is assessed by measuring the surface registration error for the fiducial and target needle tracks (FRE and TRE). This system was demonstrated in situ by injecting 200 μm tungsten beads into rat brains along oblique trajectories through a single burr hole on the top of the skull under micro-CT image guidance. Postintervention micro-CT images of each skull were registered with preintervention high-field magnetic resonance images of the brain to infer the anatomical locations of the beads. Results: Registration using four fiducial needle tracks and one target track produced a FRE and a TRE of 96 and 210 μm, respectively. Evaluation with tissue-mimicking gelatin phantoms showed that locations could be targeted with a mean error of 154±113 μm. Conclusions: The integration of a robotic needle-positioning device with volumetric micro-CT image guidance should increase the accuracy and reduce the invasiveness of stereotactic needle interventions in small animals.

Integration and evaluation of a needle-positioning robot with volumetric microcomputed tomography image guidance for small animal stereotactic interventions

Energy Technology Data Exchange (ETDEWEB)

Waspe, Adam C.; McErlain, David D.; Pitelka, Vasek; Holdsworth, David W.; Lacefield, James C.; Fenster, Aaron [Biomedical Engineering Graduate Program and Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8 (Canada); Department of Medical Biophysics and Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8 (Canada); Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario N6A 5C1 (Canada); Biomedical Engineering Graduate Program, Department of Medical Biophysics, Department of Medical Imaging, Department of Surgery, and Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8 (Canada); Biomedical Engineering Graduate Program, Department of Electrical and Computer Engineering, Department of Medical Biophysics, and Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8 (Canada); Biomedical Engineering Graduate Program, Department of Medical Biophysics, Department of Medical Imaging, and Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8 (Canada)

2010-04-15

Purpose: Preclinical research protocols often require insertion of needles to specific targets within small animal brains. To target biologically relevant locations in rodent brains more effectively, a robotic device has been developed that is capable of positioning a needle along oblique trajectories through a single burr hole in the skull under volumetric microcomputed tomography (micro-CT) guidance. Methods: An x-ray compatible stereotactic frame secures the head throughout the procedure using a bite bar, nose clamp, and ear bars. CT-to-robot registration enables structures identified in the image to be mapped to physical coordinates in the brain. Registration is accomplished by injecting a barium sulfate contrast agent as the robot withdraws the needle from predefined points in a phantom. Registration accuracy is affected by the robot-positioning error and is assessed by measuring the surface registration error for the fiducial and target needle tracks (FRE and TRE). This system was demonstrated in situ by injecting 200 {mu}m tungsten beads into rat brains along oblique trajectories through a single burr hole on the top of the skull under micro-CT image guidance. Postintervention micro-CT images of each skull were registered with preintervention high-field magnetic resonance images of the brain to infer the anatomical locations of the beads. Results: Registration using four fiducial needle tracks and one target track produced a FRE and a TRE of 96 and 210 {mu}m, respectively. Evaluation with tissue-mimicking gelatin phantoms showed that locations could be targeted with a mean error of 154{+-}113 {mu}m. Conclusions: The integration of a robotic needle-positioning device with volumetric micro-CT image guidance should increase the accuracy and reduce the invasiveness of stereotactic needle interventions in small animals.

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.

A comparative study on medical image segmentation methods

Directory of Open Access Journals (Sweden)

Praylin Selva Blessy SELVARAJ ASSLEY

2014-03-01

Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

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...

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.

Prediction of the microsurgical window for skull-base tumors by advanced three-dimensional multi-fusion volumetric imaging

International Nuclear Information System (INIS)

Oishi, Makoto; Fukuda, Masafumi; Saito, Akihiko; Hiraishi, Tetsuya; Fujii, Yukihiko; Ishida, Go

2011-01-01

The surgery of skull base tumors (SBTs) is difficult due to the complex and narrow surgical window that is restricted by the cranium and important structures. The utility of three-dimensional multi-fusion volumetric imaging (3-D MFVI) for visualizing the predicted window for SBTs was evaluated. Presurgical simulation using 3-D MFVI was performed in 32 patients with SBTs. Imaging data were collected from computed tomography, magnetic resonance imaging, and digital subtraction angiography. Skull data was processed to imitate actual bone resection and integrated with various structures extracted from appropriate imaging modalities by image-analyzing software. The simulated views were compared with the views obtained during surgery. All craniotomies and bone resections except opening of the acoustic canal in 2 patients were performed as simulated. The simulated window allowed observation of the expected microsurgical anatomies including tumors, vasculatures, and cranial nerves, through the predicted operative window. We could not achieve the planned tumor removal in only 3 patients. 3-D MFVI afforded high quality images of the relevant microsurgical anatomies during the surgery of SBTs. The intraoperative deja-vu effect of the simulation increased the confidence of the surgeon in the planned surgical procedures. (author)

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

Volumetric optoacoustic monitoring of endovenous laser treatments

Science.gov (United States)

Fehm, Thomas F.; Deán-Ben, Xosé L.; Schaur, Peter; Sroka, Ronald; Razansky, Daniel

2016-03-01

Chronic venous insufficiency (CVI) is one of the most common medical conditions with reported prevalence estimates as high as 30% in the adult population. Although conservative management with compression therapy may improve the symptoms associated with CVI, healing often demands invasive procedures. Besides established surgical methods like vein stripping or bypassing, endovenous laser therapy (ELT) emerged as a promising novel treatment option during the last 15 years offering multiple advantages such as less pain and faster recovery. Much of the treatment success hereby depends on monitoring of the treatment progression using clinical imaging modalities such as Doppler ultrasound. The latter however do not provide sufficient contrast, spatial resolution and three-dimensional imaging capacity which is necessary for accurate online lesion assessment during treatment. As a consequence, incidence of recanalization, lack of vessel occlusion and collateral damage remains highly variable among patients. In this study, we examined the capacity of volumetric optoacoustic tomography (VOT) for real-time monitoring of ELT using an ex-vivo ox foot model. ELT was performed on subcutaneous veins while optoacoustic signals were acquired and reconstructed in real-time and at a spatial resolution in the order of 200μm. VOT images showed spatio-temporal maps of the lesion progression, characteristics of the vessel wall, and position of the ablation fiber's tip during the pull back. It was also possible to correlate the images with the temperature elevation measured in the area adjacent to the ablation spot. We conclude that VOT is a promising tool for providing online feedback during endovenous laser therapy.

Impact of analyzing fewer image frames per segment during offline volumetric radiofrequency based intravascular ultrasound measurements of target lesions prior to percutaneous coronary interventions

NARCIS (Netherlands)

Huisman, J.; Hartmann, M.; Hartmann, M.; Mintz, G.S.; van Houwelingen, G.K.; Stoel, M.G.; de Man, F.H.; Louwerenburg, H.; von Birgelen, Clemens

2012-01-01

In the present study, we evaluated the impact of a 50% reduction in number of image frames (every second frame) on the analysis time and variability of offline volumetric radiofrequency-based intravascular ultrasound (RF-IVUS) measurements in target lesions prior to percutaneous coronary

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

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

Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux.

Science.gov (United States)

Lee, Jonghwan; Jiang, James Y; Wu, Weicheng; Lesage, Frederic; Boas, David A

2014-04-01

We present a novel optical coherence tomography (OCT)-based technique for rapid volumetric imaging of red blood cell (RBC) flux in capillary networks. Previously we reported that OCT can capture individual RBC passage within a capillary, where the OCT intensity signal at a voxel fluctuates when an RBC passes the voxel. Based on this finding, we defined a metric of statistical intensity variation (SIV) and validated that the mean SIV is proportional to the RBC flux [RBC/s] through simulations and measurements. From rapidly scanned volume data, we used Hessian matrix analysis to vectorize a segment path of each capillary and estimate its flux from the mean of the SIVs gathered along the path. Repeating this process led to a 3D flux map of the capillary network. The present technique enabled us to trace the RBC flux changes over hundreds of capillaries with a temporal resolution of ~1 s during functional activation.

Linking Neurons to Network Function and Behavior by Two-Photon Holographic Optogenetics and Volumetric Imaging.

Science.gov (United States)

Dal Maschio, Marco; Donovan, Joseph C; Helmbrecht, Thomas O; Baier, Herwig

2017-05-17

We introduce a flexible method for high-resolution interrogation of circuit function, which combines simultaneous 3D two-photon stimulation of multiple targeted neurons, volumetric functional imaging, and quantitative behavioral tracking. This integrated approach was applied to dissect how an ensemble of premotor neurons in the larval zebrafish brain drives a basic motor program, the bending of the tail. We developed an iterative photostimulation strategy to identify minimal subsets of channelrhodopsin (ChR2)-expressing neurons that are sufficient to initiate tail movements. At the same time, the induced network activity was recorded by multiplane GCaMP6 imaging across the brain. From this dataset, we computationally identified activity patterns associated with distinct components of the elicited behavior and characterized the contributions of individual neurons. Using photoactivatable GFP (paGFP), we extended our protocol to visualize single functionally identified neurons and reconstruct their morphologies. Together, this toolkit enables linking behavior to circuit activity with unprecedented resolution. Copyright © 2017 Elsevier Inc. All rights reserved.

Patient specific dynamic geometric models from sequential volumetric time series image data.

Science.gov (United States)

Cameron, B M; Robb, R A

2004-01-01

Generating patient specific dynamic models is complicated by the complexity of the motion intrinsic and extrinsic to the anatomic structures being modeled. Using a physics-based sequentially deforming algorithm, an anatomically accurate dynamic four-dimensional model can be created from a sequence of 3-D volumetric time series data sets. While such algorithms may accurately track the cyclic non-linear motion of the heart, they generally fail to accurately track extrinsic structural and non-cyclic motion. To accurately model these motions, we have modified a physics-based deformation algorithm to use a meta-surface defining the temporal and spatial maxima of the anatomic structure as the base reference surface. A mass-spring physics-based deformable model, which can expand or shrink with the local intrinsic motion, is applied to the metasurface, deforming this base reference surface to the volumetric data at each time point. As the meta-surface encompasses the temporal maxima of the structure, any extrinsic motion is inherently encoded into the base reference surface and allows the computation of the time point surfaces to be performed in parallel. The resultant 4-D model can be interactively transformed and viewed from different angles, showing the spatial and temporal motion of the anatomic structure. Using texture maps and per-vertex coloring, additional data such as physiological and/or biomechanical variables (e.g., mapping electrical activation sequences onto contracting myocardial surfaces) can be associated with the dynamic model, producing a 5-D model. For acquisition systems that may capture only limited time series data (e.g., only images at end-diastole/end-systole or inhalation/exhalation), this algorithm can provide useful interpolated surfaces between the time points. Such models help minimize the number of time points required to usefully depict the motion of anatomic structures for quantitative assessment of regional dynamics.

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.

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.

Intrafraction Bladder Motion in Radiation Therapy Estimated From Pretreatment and Posttreatment Volumetric Imaging

Energy Technology Data Exchange (ETDEWEB)

Foroudi, Farshad, E-mail: farshad.foroudi@petermac.org [Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria (Australia); Pham, Daniel [Radiation Therapy Services, Peter MacCallum Cancer Centre, Melbourne, Victoria (Australia); Bressel, Mathias [Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Victoria (Australia); Gill, Suki [Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria (Australia); Kron, Tomas [Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria (Australia)

2013-05-01

Purpose: The use of image guidance protocols using soft tissue anatomy identification before treatment can reduce interfractional variation. This makes intrafraction clinical target volume (CTV) to planning target volume (PTV) changes more important, including those resulting from intrafraction bladder filling and motion. The purpose of this study was to investigate the required intrafraction margins for soft tissue image guidance from pretreatment and posttreatment volumetric imaging. Methods and Materials: Fifty patients with muscle-invasive bladder cancer (T2-T4) underwent an adaptive radiation therapy protocol using daily pretreatment cone beam computed tomography (CBCT) with weekly posttreatment CBCT. A total of 235 pairs of pretreatment and posttreatment CBCT images were retrospectively contoured by a single radiation oncologist (CBCT-CTV). The maximum bladder displacement was measured according to the patient's bony pelvis movement during treatment, intrafraction bladder filling, and bladder centroid motion. Results: The mean time between pretreatment and posttreatment CBCT was 13 minutes, 52 seconds (range, 7 min 52 sec to 30 min 56 sec). Taking into account patient motion, bladder centroid motion, and bladder filling, the required margins to cover intrafraction changes from pretreatment to posttreatment in the superior, inferior, right, left, anterior, and posterior were 1.25 cm (range, 1.19-1.50 cm), 0.67 cm (range, 0.58-1.12 cm), 0.74 cm (range, 0.59-0.94 cm), 0.73 cm (range, 0.51-1.00 cm), 1.20 cm (range, 0.85-1.32 cm), and 0.86 cm (range, 0.73-0.99), respectively. Small bladders on pretreatment imaging had relatively the largest increase in pretreatment to posttreatment volume. Conclusion: Intrafraction motion of the bladder based on pretreatment and posttreatment bladder imaging can be significant particularly in the anterior and superior directions. Patient motion, bladder centroid motion, and bladder filling all contribute to changes between

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

Frontal-subcortical volumetric deficits in single episode, medication-naïve depressed patients and the effects of 8 weeks fluoxetine treatment: a VBM-DARTEL study.

Directory of Open Access Journals (Sweden)

Lingtao Kong

Full Text Available BACKGROUND: Convergent studies suggest that morphological abnormalities of frontal-subcortical circuits which involved with emotional and cognitive processing may contribute to the pathophysiology of major depressive disorder (MDD. Antidepressant treatment which has been reported to reverse the functional abnormalities of frontal-subcortical circuits in MDD may have treating effects to related brain morphological abnormalities. In this study, we used voxel-based morphometry method to investigate whole brain structural abnormalities in single episode, medication-naïve MDD patients. Furthermore, we investigated the effects of an 8 weeks pharmacotherapy with fluoxetine. METHODS: 28 single episode, medication-naïve MDD participants and 28 healthy controls (HC acquired the baseline high-resolution structural magnetic resonance imaging (sMRI scan. 24 MDD participants acquired a follow-up sMRI scan after 8 weeks antidepressant treatment. Gray matter volumetric (GMV difference between groups was examined. RESULTS: Medication-naïve MDD had significantly decreased GMV in the right dorsolateral prefrontal cortex and left middle frontal gyrus as well as increased GMV in the left thalamus and right insula compared to HC (P<0.05, corrected. Moreover, treated MDD had significantly increased GMV in the left middle frontal gyrus and right orbitofrontal cortex compared to HC (P<0.05, corrected. No difference on GMV was detected between medication-naïve MDD group and treated MDD group. CONCLUSIONS: This study of single episode, medication-naïve MDD subjects demonstrated structural abnormalities of frontal-subcortical circuitsin the early stage of MDD and the effects of 8 weeks successful antidepressant treatment, suggesting these abnormalities may play an important role in the neuropathophysiology of MDD at its onset.

Lossless medical image compression with a hybrid coder

Science.gov (United States)

Way, Jing-Dar; Cheng, Po-Yuen

1998-10-01

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

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...

3D Tendon Strain Estimation Using High-frequency Volumetric Ultrasound Images: A Feasibility Study.

Science.gov (United States)

Carvalho, Catarina; Slagmolen, Pieter; Bogaerts, Stijn; Scheys, Lennart; D'hooge, Jan; Peers, Koen; Maes, Frederik; Suetens, Paul

2018-03-01

Estimation of strain in tendons for tendinopathy assessment is a hot topic within the sports medicine community. It is believed that, if accurately estimated, existing treatment and rehabilitation protocols can be improved and presymptomatic abnormalities can be detected earlier. State-of-the-art studies present inaccurate and highly variable strain estimates, leaving this problem without solution. Out-of-plane motion, present when acquiring two-dimensional (2D) ultrasound (US) images, is a known problem and may be responsible for such errors. This work investigates the benefit of high-frequency, three-dimensional (3D) US imaging to reduce errors in tendon strain estimation. Volumetric US images were acquired in silico, in vitro, and ex vivo using an innovative acquisition approach that combines the acquisition of 2D high-frequency US images with a mechanical guided system. An affine image registration method was used to estimate global strain. 3D strain estimates were then compared with ground-truth values and with 2D strain estimates. The obtained results for in silico data showed a mean absolute error (MAE) of 0.07%, 0.05%, and 0.27% for 3D estimates along axial, lateral direction, and elevation direction and a respective MAE of 0.21% and 0.29% for 2D strain estimates. Although 3D could outperform 2D, this does not occur in in vitro and ex vivo settings, likely due to 3D acquisition artifacts. Comparison against the state-of-the-art methods showed competitive results. The proposed work shows that 3D strain estimates are more accurate than 2D estimates but acquisition of appropriate 3D US images remains a challenge.

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.

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.

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.

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.

Prototype volumetric ultrasound tomography image guidance system for prone stereotactic partial breast irradiation: proof-of-concept

Science.gov (United States)

Chiu, Tsuicheng D.; Parsons, David; Zhang, Yue; Hrycushko, Brian; Zhao, Bo; Chopra, Rajiv; Kim, Nathan; Spangler, Ann; Rahimi, Asal; Timmerman, Robert; Jiang, Steve B.; Lu, Weiguo; Gu, Xuejun

2018-03-01

Accurate dose delivery in stereotactic partial breast irradiation (S-PBI) is challenging because of the target position uncertainty caused by breast deformation, the target volume changes caused by lumpectomy cavity shrinkage, and the target delineation uncertainty on simulation computed tomography (CT) images caused by poor soft tissue contrast. We have developed a volumetric ultrasound tomography (UST) image guidance system for prone position S-PBI. The system is composed of a novel 3D printed rotation water tank, a patient-specific resin breast immobilization cup, and a 1D array ultrasound transducer. Coronal 2D US images were acquired in 5° increments over a 360° range, and planes were acquired every 2 mm in elevation. A super-compounding technique was used to reconstruct the image volume. The image quality of UST was evaluated with a BB-1 breast phantom and BioZorb surgical marker, and the results revealed that UST offered better soft tissue contrast than CT and similar image quality to MR. In the evaluated plane, the size and location of five embedded objects were measured and compared to MR, which is considered as the ground truth. Objects’ diameters and the distances between objects in UST differ by approximately 1 to 2 mm from those in MR, which showed that UST offers the image quality required for S-PBI. In future work we will develop a robotic system that will be ultimately implemented in the clinic.

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 Imaging: A New Frontier in Medical Imaging

OpenAIRE

Bijan Bijan

2010-01-01

Introduction of hybrid imaging in the arena of medical imaging calls for re-strategizing in current practice. Operating PET-CT and upcoming PET-MRI is a turf battle between Radiologists, Nuclear Medicine Physicians, Oncologists, Cardiologists and other related fields.

Volumetric capnography: In the diagnostic work-up of chronic thromboembolic disease

Directory of Open Access Journals (Sweden)

Marcos Mello Moreira

2010-05-01

Full Text Available Marcos Mello Moreira1, Renato Giuseppe Giovanni Terzi1, Laura Cortellazzi2, Antonio Luis Eiras Falcão1, Heitor Moreno Junior2, Luiz Cláudio Martins2, Otavio Rizzi Coelho21Department of Surgery, 2Department of Internal Medicine, State University of Campinas, School of Medical Sciences, Campinas, Sao Paulo, BrazilAbstract: The morbidity and mortality of pulmonary embolism (PE have been found to be related to early diagnosis and appropriate treatment. The examinations used to diagnose PE are expensive and not always easily accessible. These options include noninvasive examinations, such as clinical pretests, ELISA D-dimer (DD tests, and volumetric capnography (VCap. We report the case of a patient whose diagnosis of PE was made via pulmonary arteriography. The clinical pretest revealed a moderate probability of the patient having PE, and the DD result was negative; however, the VCap associated with arterial blood gases result was positive. The patient underwent all noninvasive exams following admission to hospital and again eight months after discharge. Results gained from invasive tests were similar to those produced by image exams, highlighting the importance of VCap as an important noninvasive tool.Keywords: pulmonary embolism, pulmonary hypertension, volumetric capnography, d-dimers, pretest probability

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...

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.)

Inkjet printing-based volumetric display projecting multiple full-colour 2D patterns

Science.gov (United States)

Hirayama, Ryuji; Suzuki, Tomotaka; Shimobaba, Tomoyoshi; Shiraki, Atsushi; Naruse, Makoto; Nakayama, Hirotaka; Kakue, Takashi; Ito, Tomoyoshi

2017-04-01

In this study, a method to construct a full-colour volumetric display is presented using a commercially available inkjet printer. Photoreactive luminescence materials are minutely and automatically printed as the volume elements, and volumetric displays are constructed with high resolution using easy-to-fabricate means that exploit inkjet printing technologies. The results experimentally demonstrate the first prototype of an inkjet printing-based volumetric display composed of multiple layers of transparent films that yield a full-colour three-dimensional (3D) image. Moreover, we propose a design algorithm with 3D structures that provide multiple different 2D full-colour patterns when viewed from different directions and experimentally demonstrate prototypes. It is considered that these types of 3D volumetric structures and their fabrication methods based on widely deployed existing printing technologies can be utilised as novel information display devices and systems, including digital signage, media art, entertainment and security.

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.

Comparison of the image quality between volumetric and conventional high-resolution CT with 64-slice row CT

International Nuclear Information System (INIS)

Gao Yanli; Zhang Lei; Zhao Xia; Ma Min; Zhai Renyou

2008-01-01

Objective: To compare the image quality between volumetric high-resolution CT (VHRCT) and conventional high-resolution CT (CHRCT), and investigate the feasibility of VHRCT. Methods: Catphan 412 phantom was scanned with protocols of CHRCT and VHRCT on a set of GE Lightspeed VCT. The spatial-resolution (LP/cm), noise (standard deviation in an ROI) and radiation close (CTDI) were recorded for each CT scan. Difference of noise between CHRCT and VHRCT were evaluated by paired t test. In clinical study, 32 patients were scanned with VHRCT and CHRCT protocols. The image quality of CHRCT and VHRCT was rated and compared. The quality difference between CHRCT and VHRCT was assessed by Wilcoxon paired signed rank sum test. Results: In phantom study, the in-plane spatial-resolution of both VHRCT and CHRCT was 11 LP/cm for axial images and 12 LP/cm for coronal reformatted images. The noise of VHRCT and CHRCT was (69.18±2.77)HU and (54.62±2.12) HU respectively (t=-15.929, P 0.05). The quality assessment scores of VHRCT coronal reformatted images and CHRCT coronal reformatted images were 3.05 and 1.88 respectively with significant difference (Z= -5.088, P<0.01). Conclusion: The image quality of VHRCT cross-sectional image is similar to that of CHRCT. Multiplanar images with high resolution of VHRCT are recommended. The radiation dose of VHRCT remains to be optimized. (authors)

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.

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.

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.

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.

Lesion removal and lesion addition algorithms in lung volumetric data sets for perception studies

Science.gov (United States)

Madsen, Mark T.; Berbaum, Kevin S.; Ellingson, Andrew; Thompson, Brad H.; Mullan, Brian F.

2006-03-01

Image perception studies of medical images provide important information about how radiologists interpret images and insights for reducing reading errors. In the past, perception studies have been difficult to perform using clinical imaging studies because of the problems associated with obtaining images demonstrating proven abnormalities and appropriate normal control images. We developed and evaluated interactive software that allows the seamless removal of abnormal areas from CT lung image sets. We have also developed interactive software for capturing lung lesions in a database where they can be added to lung CT studies. The efficacy of the software to remove abnormal areas of lung CT studies was evaluated psychophysically by having radiologists select the one altered image from a display of four. The software for adding lesions was evaluated by having radiologists classify displayed CT slices with lesions as real or artificial scaled to 3 levels of confidence. The results of these experiments demonstrated that the radiologist had difficulty in distinguishing the raw clinical images from those that had been altered. We conclude that this software can be used to create experimental normal control and "proven" lesion data sets for volumetric CT of the lung fields. We also note that this software can be easily adapted to work with other tissue besides lung and that it can be adapted to other digital imaging modalities.

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...

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.

What are the potential advantages and disadvantages of volumetric CT scanning?

Science.gov (United States)

Voros, Szilard

2009-01-01

After the introduction and dissemination of 64-slice multislice computed tomography systems, cardiovascular CT has arrived at a crossroad, and different philosophies lead down different paths of technologic development. Increased number of detector rows in the z-axis led to the introduction of dynamic, volumetric scanning of the heart and allows for whole-organ imaging. Dynamic, volumetric "whole-organ" scanning significantly reduces image acquisition time; "single-beat whole-heart imaging" results in improved image quality and reduced radiation exposure and reduced contrast dose. It eliminates helical and pitch artifacts and allows for simultaneous imaging of the base and apex of the heart. Beyond coronary arterial luminal imaging, such innovations open up the opportunity for myocardial perfusion and viability imaging and coronary arterial plaque imaging. Dual-source technology with 2 x-ray tubes placed at 90-degree angles provides heart rate-independent temporal resolution and has the potential for tissue characterization on the basis of different attenuation values at different energy levels. Refined detector technology allows for improved low-contrast resolution and may be beneficial for more detailed evaluation of coronary arterial plaque composition. The clinical benefit of each of these technologies will have to be evaluated in carefully designed clinical trials and in everyday clinical practice. Such combined experience will probably show the relative benefit of each of these philosophies in different patient populations and in different clinical scenarios.

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...

Optical Addressing of Multi-Colour Photochromic Material Mixture for Volumetric Display

Science.gov (United States)

Hirayama, Ryuji; Shiraki, Atsushi; Naruse, Makoto; Nakamura, Shinichiro; Nakayama, Hirotaka; Kakue, Takashi; Shimobaba, Tomoyoshi; Ito, Tomoyoshi

2016-08-01

This is the first study to demonstrate that colour transformations in the volume of a photochromic material (PM) are induced at the intersections of two control light channels, one controlling PM colouration and the other controlling decolouration. Thus, PM colouration is induced by position selectivity, and therefore, a dynamic volumetric display may be realised using these two control lights. Moreover, a mixture of multiple PM types with different absorption properties exhibits different colours depending on the control light spectrum. Particularly, the spectrum management of the control light allows colour-selective colouration besides position selectivity. Therefore, a PM-based, full-colour volumetric display is realised. We experimentally construct a mixture of two PM types and validate the operating principles of such a volumetric display system. Our system is constructed simply by mixing multiple PM types; therefore, the display hardware structure is extremely simple, and the minimum size of a volume element can be as small as the size of a molecule. Volumetric displays can provide natural three-dimensional (3D) perception; therefore, the potential uses of our system include high-definition 3D visualisation for medical applications, architectural design, human-computer interactions, advertising, and entertainment.

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

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)

SU-D-18A-02: Towards Real-Time On-Board Volumetric Image Reconstruction for Intrafraction Target Verification in Radiation Therapy

International Nuclear Information System (INIS)

Xu, X; Iliopoulos, A; Zhang, Y; Pitsianis, N; Sun, X; Yin, F; Ren, L

2014-01-01

Purpose: To expedite on-board volumetric image reconstruction from limited-angle kV—MV projections for intrafraction verification. Methods: A limited-angle intrafraction verification (LIVE) system has recently been developed for real-time volumetric verification of moving targets, using limited-angle kV—MV projections. Currently, it is challenged by the intensive computational load of the prior-knowledge-based reconstruction method. To accelerate LIVE, we restructure the software pipeline to make it adaptable to model and algorithm parameter changes, while enabling efficient utilization of rapidly advancing, modern computer architectures. In particular, an innovative two-level parallelization scheme has been designed: At the macroscopic level, data and operations are adaptively partitioned, taking into account algorithmic parameters and the processing capacity or constraints of underlying hardware. The control and data flows of the pipeline are scheduled in such a way as to maximize operation concurrency and minimize total processing time. At the microscopic level, the partitioned functions act as independent modules, operating on data partitions in parallel. Each module is pre-parallelized and optimized for multi-core processors (CPUs) and graphics processing units (GPUs). Results: We present results from a parallel prototype, where most of the controls and module parallelization are carried out via Matlab and its Parallel Computing Toolbox. The reconstruction is 5 times faster on a data-set of twice the size, compared to recently reported results, without compromising on algorithmic optimization control. Conclusion: The prototype implementation and its results have served to assess the efficacy of our system concept. While a production implementation will yield much higher processing rates by approaching full-capacity utilization of CPUs and GPUs, some mutual constraints between algorithmic flow and architecture specifics remain. Based on a careful analysis

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.

A prototype table-top inverse-geometry volumetric CT system

International Nuclear Information System (INIS)

Schmidt, Taly Gilat; Star-Lack, Josh; Bennett, N. Robert; Mazin, Samuel R.; Solomon, Edward G.; Fahrig, Rebecca; Pelc, Norbert J.

2006-01-01

A table-top volumetric CT system has been implemented that is able to image a 5-cm-thick volume in one circular scan with no cone-beam artifacts. The prototype inverse-geometry CT (IGCT) scanner consists of a large-area, scanned x-ray source and a detector array that is smaller in the transverse direction. The IGCT geometry provides sufficient volumetric sampling because the source and detector have the same axial, or slice direction, extent. This paper describes the implementation of the table-top IGCT scanner, which is based on the NexRay Scanning-Beam Digital X-ray system (NexRay, Inc., Los Gatos, CA) and an investigation of the system performance. The alignment and flat-field calibration procedures are described, along with a summary of the reconstruction algorithm. The resolution and noise performance of the prototype IGCT system are studied through experiments and further supported by analytical predictions and simulations. To study the presence of cone-beam artifacts, a ''Defrise'' phantom was scanned on both the prototype IGCT scanner and a micro CT system with a ±5 deg.cone angle for a 4.5-cm volume thickness. Images of inner ear specimens are presented and compared to those from clinical CT systems. Results showed that the prototype IGCT system has a 0.25-mm isotropic resolution and that noise comparable to that from a clinical scanner with equivalent spatial resolution is achievable. The measured MTF and noise values agreed reasonably well with theoretical predictions and computer simulations. The IGCT system was able to faithfully reconstruct the laminated pattern of the Defrise phantom while the micro CT system suffered severe cone-beam artifacts for the same object. The inner ear acquisition verified that the IGCT system can image a complex anatomical object, and the resulting images exhibited more high-resolution details than the clinical CT acquisition. Overall, the successful implementation of the prototype system supports the IGCT concept for

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.)

Daily Megavoltage Computed Tomography in Lung Cancer Radiotherapy: Correlation Between Volumetric Changes and Local Outcome

International Nuclear Information System (INIS)

Bral, Samuel; De Ridder, Mark; Duchateau, Michael; Gevaert, Thierry; Engels, Benedikt; Schallier, Denis; Storme, Guy

2011-01-01

Purpose: To assess the predictive or comparative value of volumetric changes, measured on daily megavoltage computed tomography during radiotherapy for lung cancer. Patients and Methods: We included 80 patients with locally advanced non-small-cell lung cancer treated with image-guided intensity-modulated radiotherapy. The radiotherapy was combined with concurrent chemotherapy, combined with induction chemotherapy, or given as primary treatment. Patients entered two parallel studies with moderately hypofractionated radiotherapy. Tumor volume contouring was done on the daily acquired images. A regression coefficient was derived from the volumetric changes on megavoltage computed tomography, and its predictive value was validated. Logarithmic or polynomial fits were applied to the intratreatment changes to compare the different treatment schedules radiobiologically. Results: Regardless of the treatment type, a high regression coefficient during radiotherapy predicted for a significantly prolonged cause-specific local progression free-survival (p = 0.05). Significant differences were found in the response during radiotherapy. The significant difference in volumetric treatment response between radiotherapy with concurrent chemotherapy and radiotherapy plus induction chemotherapy translated to a superior long-term local progression-free survival for concurrent chemotherapy (p = 0.03). An enhancement ratio of 1.3 was measured for the used platinum/taxane doublet in comparison with radiotherapy alone. Conclusion: Contouring on daily megavoltage computed tomography images during radiotherapy enabled us to predict the efficacy of a given treatment. The significant differences in volumetric response between treatment strategies makes it a possible tool for future schedule comparison.

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

The analysis of colour uniformity for a volumetric display based on a rotating LED array

International Nuclear Information System (INIS)

Wu, Jiang; Liu, Xu; Yan, Caijie; Xia, XinXing; Li, Haifeng

2011-01-01

There is a colour nonuniformity zone existing in three-dimensional (3D) volumetric displays which is based on the rotating colour light-emitting diode (LED) array. We analyse the reason for the colour nonuniformity zone by measuring the light intensity distribution and chromaticity coordinates of the LED in the volumetric display. Two boundaries of the colour nonuniformity zone are calculated. We measure the colour uniformities for a single cuboid of 3*3*4 voxels to display red, green, blue and white colour in different horizontal viewing angles, and for 64 cuboids distributed in the whole cylindrical image space with a fixed viewpoint. To evaluate the colour uniformity of a 3D image, we propose three evaluation indices of colour uniformity: the average of colour difference, the maximum colour difference and the variance of colour difference. The measurement results show that the character of colour uniformity is different for the 3D volumetric display and the two-dimensional display

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

Volumetric multimodality neural network for brain tumor segmentation

Science.gov (United States)

Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

Volumetric 3D display with multi-layered active screens for enhanced the depth perception (Conference Presentation)

Science.gov (United States)

Kim, Hak-Rin; Park, Min-Kyu; Choi, Jun-Chan; Park, Ji-Sub; Min, Sung-Wook

2016-09-01

Three-dimensional (3D) display technology has been studied actively because it can offer more realistic images compared to the conventional 2D display. Various psychological factors such as accommodation, binocular parallax, convergence and motion parallax are used to recognize a 3D image. For glass-type 3D displays, they use only the binocular disparity in 3D depth cues. However, this method cause visual fatigue and headaches due to accommodation conflict and distorted depth perception. Thus, the hologram and volumetric display are expected to be an ideal 3D display. Holographic displays can represent realistic images satisfying the entire factors of depth perception. But, it require tremendous amount of data and fast signal processing. The volumetric 3D displays can represent images using voxel which is a physical volume. However, it is required for large data to represent the depth information on voxel. In order to simply encode 3D information, the compact type of depth fused 3D (DFD) display, which can create polarization distributed depth map (PDDM) image having both 2D color image and depth image is introduced. In this paper, a new volumetric 3D display system is shown by using PDDM image controlled by polarization controller. In order to introduce PDDM image, polarization states of the light through spatial light modulator (SLM) was analyzed by Stokes parameter depending on the gray level. Based on the analysis, polarization controller is properly designed to convert PDDM image into sectioned depth images. After synchronizing PDDM images with active screens, we can realize reconstructed 3D image. Acknowledgment This work was supported by `The Cross-Ministry Giga KOREA Project' grant from the Ministry of Science, ICT and Future Planning, Korea

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.

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.

Neural networks: Application to medical imaging

Science.gov (United States)

Clarke, Laurence P.

1994-01-01

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

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.

In-situ volumetric topography of IC chips for defect detection using infrared confocal measurement with active structured light

International Nuclear Information System (INIS)

Chen, Liang-Chia; Le, Manh-Trung; Phuc, Dao Cong; Lin, Shyh-Tsong

2014-01-01

The article presents the development of in-situ integrated circuit (IC) chip defect detection techniques for automated clipping detection by proposing infrared imaging and full-field volumetric topography. IC chip inspection, especially held during or post IC packaging, has become an extremely critical procedure in IC fabrication to assure manufacturing quality and reduce production costs. To address this, in the article, microscopic infrared imaging using an electromagnetic light spectrum that ranges from 0.9 to 1.7 µm is developed to perform volumetric inspection of IC chips, in order to identify important defects such as silicon clipping, cracking or peeling. The main difficulty of infrared (IR) volumetric imaging lies in its poor image contrast, which makes it incapable of achieving reliable inspection, as infrared imaging is sensitive to temperature difference but insensitive to geometric variance of materials, resulting in difficulty detecting and quantifying defects precisely. To overcome this, 3D volumetric topography based on 3D infrared confocal measurement with active structured light, as well as light refractive matching principles, is developed to detect defects the size, shape and position of defects in ICs. The experimental results show that the algorithm is effective and suitable for in-situ defect detection of IC semiconductor packaging. The quality of defect detection, such as measurement repeatability and accuracy, is addressed. Confirmed by the experimental results, the depth measurement resolution can reach up to 0.3 µm, and the depth measurement uncertainty with one standard deviation was verified to be less than 1.0% of the full-scale depth-measuring range. (paper)

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...

The importance of accurate anatomic assessment for the volumetric analysis of the amygdala

Directory of Open Access Journals (Sweden)

L. Bonilha

2005-03-01

Full Text Available There is a wide range of values reported in volumetric studies of the amygdala. The use of single plane thick magnetic resonance imaging (MRI may prevent the correct visualization of anatomic landmarks and yield imprecise results. To assess whether there is a difference between volumetric analysis of the amygdala performed with single plane MRI 3-mm slices and with multiplanar analysis of MRI 1-mm slices, we studied healthy subjects and patients with temporal lobe epilepsy. We performed manual delineation of the amygdala on T1-weighted inversion recovery, 3-mm coronal slices and manual delineation of the amygdala on three-dimensional volumetric T1-weighted images with 1-mm slice thickness. The data were compared using a dependent t-test. There was a significant difference between the volumes obtained by the coronal plane-based measurements and the volumes obtained by three-dimensional analysis (P < 0.001. An incorrect estimate of the amygdala volume may preclude a correct analysis of the biological effects of alterations in amygdala volume. Three-dimensional analysis is preferred because it is based on more extensive anatomical assessment and the results are similar to those obtained in post-mortem studies.

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.

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

Directory of Open Access Journals (Sweden)

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.

In vivo evaluation of biosensors volumetric bio-distribution for measurement of metabolic activity by X-ray correlation, fluorescence, Cerenkov image and radioisotope; Evaluacion in vivo de la biodistribucion volumetrica de biosensores para medicion de la actividad metabolica por correlacion de rayos X, fluorescencia, imagen Cerenkov y radioisotopica

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Ramirez N, G. J.

2016-07-01

The aim of this study was to characterize the in vivo volumetric distribution of three folate based biosensors by different imaging modalities (X-ray, fluorescence, Cerenkov luminescence and radioisotopic imaging) through the development of a tri dimensional (3D) image reconstruction algorithm. The preclinical and multimodal Xtreme imaging system, with a Multimodal Animal Rotation System (Mars), was used to acquire bidimensional (2D) images, which were processed to obtain the 3D reconstruction. Images of mice at different times (biosensor distribution) were simultaneously obtained from the four imaging modalities. The filtered backprojection and inverse Radon transformation were used as main image-processing techniques. In the first instance, the algorithm developed in Mat lab was able to reconstruct in the 3D form the skeleton of the mice under study. Subsequently, the algorithm was able to get the volumetric profiles of {sup 99m}Tc-Folate-Bombesin (radioisotopic image), {sup 177}Lu-Folate-Bombesin (Cerenkov image), and FolateRSense 680 (fluorescence image) in the tumors and kidneys of the mice. No significant differences were detected between the volumetric quantifications using the standard measurement techniques and the quantifications obtained with the proposal made in this study, nor between the volumetric uptakes in the structures of interest. With the structures reconstructed in the 3D form, the fusion of anatomical (as the skeleton) and functional structures derived from the images of the biosensors uptake was achieved The imaging 3D reconstruction algorithm can be easily extrapolated to different 2D acquisition-type images. This characteristic flexibility of the algorithm developed in this study is an advantage in comparison to similar reconstruction methods. (Author)

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Energy Technology Data Exchange (ETDEWEB)

Seibert, Tyler M.; Karunamuni, Roshan [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California (United States); Bartsch, Hauke [Department of Radiology, University of California, San Diego, La Jolla, California (United States); Kaifi, Samar [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California (United States); Krishnan, Anitha Priya [Department of Radiology, University of California, San Diego, La Jolla, California (United States); Dalia, Yoseph; Burkeen, Jeffrey; Murzin, Vyacheslav; Moiseenko, Vitali [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California (United States); Kuperman, Joshua; White, Nathan S. [Department of Radiology, University of California, San Diego, La Jolla, California (United States); Brewer, James B. [Department of Radiology, University of California, San Diego, La Jolla, California (United States); Department of Neurosciences, University of California, San Diego, La Jolla, California (United States); Farid, Nikdokht [Department of Radiology, University of California, San Diego, La Jolla, California (United States); McDonald, Carrie R. [Department of Psychiatry, University of California, San Diego, La Jolla, California (United States); Hattangadi-Gluth, Jona A., E-mail: jhattangadi@ucsd.edu [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California (United States)

2017-02-01

Purpose: After radiation therapy (RT) to the brain, patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy. Methods and Materials: Hippocampal volume was measured with magnetic resonance imaging (MRI) in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3-dimensional volumetric MRI before and 1 year after RT. Images were processed using software with clearance from the US Food and Drug Administration and Conformité Européene marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy 1 year after RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (<10 Gy) mean RT dose. A multivariate analysis was conducted with linear mixed-effects modeling to evaluate other potential predictors of hippocampal volume change, including patient (random effect), age, hemisphere, sex, seizure history, and baseline volume. Statistical significance was evaluated at α = 0.05. Results: Mean hippocampal dose was significantly correlated with hippocampal volume loss (r=−0.24, P=.03). Mean hippocampal volume was significantly reduced 1 year after high-dose RT (mean −6%, P=.009) but not after low-dose RT. In multivariate analysis, both RT dose and patient age were significant predictors of hippocampal atrophy (P<.01). Conclusions: The hippocampus demonstrates radiation dose–dependent atrophy after treatment for brain

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.

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.

Volumetric spiral chemical shift imaging of hyperpolarized [2-(13) c]pyruvate in a rat c6 glioma model.

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Park, Jae Mo; Josan, Sonal; Jang, Taichang; Merchant, Milton; Watkins, Ron; Hurd, Ralph E; Recht, Lawrence D; Mayer, Dirk; Spielman, Daniel M

2016-03-01

MRS of hyperpolarized [2-(13)C]pyruvate can be used to assess multiple metabolic pathways within mitochondria as the (13)C label is not lost with the conversion of pyruvate to acetyl-CoA. This study presents the first MR spectroscopic imaging of hyperpolarized [2-(13)C]pyruvate in glioma-bearing brain. Spiral chemical shift imaging with spectrally undersampling scheme (1042 Hz) and a hard-pulse excitation was exploited to simultaneously image [2-(13)C]pyruvate, [2-(13)C]lactate, and [5-(13)C]glutamate, the metabolites known to be produced in brain after an injection of hyperpolarized [2-(13)C]pyruvate, without chemical shift displacement artifacts. A separate undersampling scheme (890 Hz) was also used to image [1-(13)C]acetyl-carnitine. Healthy and C6 glioma-implanted rat brains were imaged at baseline and after dichloroacetate administration, a drug that modulates pyruvate dehydrogenase kinase activity. The baseline metabolite maps showed higher lactate and lower glutamate in tumor as compared to normal-appearing brain. Dichloroacetate led to an increase in glutamate in both tumor and normal-appearing brain. Dichloroacetate-induced %-decrease of lactate/glutamate was comparable to the lactate/bicarbonate decrease from hyperpolarized [1-(13)C]pyruvate studies. Acetyl-carnitine was observed in the muscle/fat tissue surrounding the brain. Robust volumetric imaging with hyperpolarized [2-(13)C]pyruvate and downstream products was performed in glioma-bearing rat brains, demonstrating changes in mitochondrial metabolism with dichloroacetate. © 2015 Wiley Periodicals, Inc.

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

Semi-automated volumetric analysis of artificial lymph nodes in a phantom study

International Nuclear Information System (INIS)

Fabel, M.; Biederer, J.; Jochens, A.; Bornemann, L.; Soza, G.; Heller, M.; Bolte, H.

2011-01-01

Purpose: Quantification of tumour burden in oncology requires accurate and reproducible image evaluation. The current standard is one-dimensional measurement (e.g. RECIST) with inherent disadvantages. Volumetric analysis is discussed as an alternative for therapy monitoring of lung and liver metastases. The aim of this study was to investigate the accuracy of semi-automated volumetric analysis of artificial lymph node metastases in a phantom study. Materials and methods: Fifty artificial lymph nodes were produced in a size range from 10 to 55 mm; some of them enhanced using iodine contrast media. All nodules were placed in an artificial chest phantom (artiCHEST ® ) within different surrounding tissues. MDCT was performed using different collimations (1–5 mm) at varying reconstruction kernels (B20f, B40f, B60f). Volume and RECIST measurements were performed using Oncology Software (Siemens Healthcare, Forchheim, Germany) and were compared to reference volume and diameter by calculating absolute percentage errors. Results: The software performance allowed a robust volumetric analysis in a phantom setting. Unsatisfying segmentation results were frequently found for native nodules within surrounding muscle. The absolute percentage error (APE) for volumetric analysis varied between 0.01 and 225%. No significant differences were seen between different reconstruction kernels. The most unsatisfactory segmentation results occurred in higher slice thickness (4 and 5 mm). Contrast enhanced lymph nodes showed better segmentation results by trend. Conclusion: The semi-automated 3D-volumetric analysis software tool allows a reliable and convenient segmentation of artificial lymph nodes in a phantom setting. Lymph nodes adjacent to tissue of similar density cause segmentation problems. For volumetric analysis of lymph node metastases in clinical routine a slice thickness of ≤3 mm and a medium soft reconstruction kernel (e.g. B40f for Siemens scan systems) may be a suitable

Multi-channel medical imaging system

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters).

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Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-07

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40

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

Science.gov (United States)

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.

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

International Nuclear Information System (INIS)

Mejia, J.; Galvis-Alonso, O.Y.; Braga, J.; Correa, R.; Leite, J.P.; Simoes, M.V.

2009-01-01

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multi pinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target's radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals. (author)

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Energy Technology Data Exchange (ETDEWEB)

Mejia, J.; Galvis-Alonso, O.Y. [Faculdade de Medicina de Sao Jose do Rio Preto (FAMERP), SP (Brazil). Faculdade de Medicina. Dept. de Biologia Molecular], e-mail: mejia_famerp@yahoo.com.br; Braga, J. [Faculdade de Medicina de Sao Jose do Rio Preto (FAMERP), SP (Brazil). Div. de Astrofisica; Correa, R. [Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, SP (Brazil). Div. de Ciencia Espacial e Atmosferica; Leite, J.P. [Faculdade de Medicina de Sao Jose do Rio Preto (FAMERP), SP (Brazil). Dept. de Neurologia, Psiquiatria e Psicologia Medica; Simoes, M.V. [Faculdade de Medicina de Sao Jose do Rio Preto (FAMERP), SP (Brazil). Dept. de Clinica Medica

2009-08-15

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multi pinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target's radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals. (author)

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Directory of Open Access Journals (Sweden)

J. Mejia

2009-08-01

Full Text Available Single-photon emission computed tomography (SPECT is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.

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

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.

SU-F-J-166: Volumetric Spatial Distortions Comparison for 1.5 Tesla Versus 3 Tesla MRI for Gamma Knife Radiosurgery Scans Using Frame Marker Fusion and Co-Registration Modes

International Nuclear Information System (INIS)

Neyman, G

2016-01-01

Purpose: To compare typical volumetric spatial distortions for 1.5 Tesla versus 3 Tesla MRI Gamma Knife radiosurgery scans in the frame marker fusion and co-registration frame-less modes. Methods: Quasar phantom by Modus Medical Devices Inc. with GRID image distortion software was used for measurements of volumetric distortions. 3D volumetric T1 weighted scans of the phantom were produced on 1.5 T Avanto and 3 T Skyra MRI Siemens scanners. The analysis was done two ways: for scans with localizer markers from the Leksell frame and relatively to the phantom only (simulated co-registration technique). The phantom grid contained a total of 2002 vertices or control points that were used in the assessment of volumetric geometric distortion for all scans. Results: Volumetric mean absolute spatial deviations relatively to the frame localizer markers for 1.5 and 3 Tesla machine were: 1.39 ± 0.15 and 1.63 ± 0.28 mm with max errors of 1.86 and 2.65 mm correspondingly. Mean 2D errors from the Gamma Plan were 0.3 and 1.0 mm. For simulated co-registration technique the volumetric mean absolute spatial deviations relatively to the phantom for 1.5 and 3 Tesla machine were: 0.36 ± 0.08 and 0.62 ± 0.13 mm with max errors of 0.57 and 1.22 mm correspondingly. Conclusion: Volumetric spatial distortions are lower for 1.5 Tesla versus 3 Tesla MRI machines localized with markers on frames and significantly lower for co-registration techniques with no frame localization. The results show the advantage of using co-registration technique for minimizing MRI volumetric spatial distortions which can be especially important for steep dose gradient fields typically used in Gamma Knife radiosurgery. Consultant for Elekta AB

SU-F-J-166: Volumetric Spatial Distortions Comparison for 1.5 Tesla Versus 3 Tesla MRI for Gamma Knife Radiosurgery Scans Using Frame Marker Fusion and Co-Registration Modes

Energy Technology Data Exchange (ETDEWEB)

Neyman, G [The Cleveland Clinic Foundation, Cleveland, OH (United States)

2016-06-15

Purpose: To compare typical volumetric spatial distortions for 1.5 Tesla versus 3 Tesla MRI Gamma Knife radiosurgery scans in the frame marker fusion and co-registration frame-less modes. Methods: Quasar phantom by Modus Medical Devices Inc. with GRID image distortion software was used for measurements of volumetric distortions. 3D volumetric T1 weighted scans of the phantom were produced on 1.5 T Avanto and 3 T Skyra MRI Siemens scanners. The analysis was done two ways: for scans with localizer markers from the Leksell frame and relatively to the phantom only (simulated co-registration technique). The phantom grid contained a total of 2002 vertices or control points that were used in the assessment of volumetric geometric distortion for all scans. Results: Volumetric mean absolute spatial deviations relatively to the frame localizer markers for 1.5 and 3 Tesla machine were: 1.39 ± 0.15 and 1.63 ± 0.28 mm with max errors of 1.86 and 2.65 mm correspondingly. Mean 2D errors from the Gamma Plan were 0.3 and 1.0 mm. For simulated co-registration technique the volumetric mean absolute spatial deviations relatively to the phantom for 1.5 and 3 Tesla machine were: 0.36 ± 0.08 and 0.62 ± 0.13 mm with max errors of 0.57 and 1.22 mm correspondingly. Conclusion: Volumetric spatial distortions are lower for 1.5 Tesla versus 3 Tesla MRI machines localized with markers on frames and significantly lower for co-registration techniques with no frame localization. The results show the advantage of using co-registration technique for minimizing MRI volumetric spatial distortions which can be especially important for steep dose gradient fields typically used in Gamma Knife radiosurgery. Consultant for Elekta AB.

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)

Breast Density Estimation with Fully Automated Volumetric Method: Comparison to Radiologists' Assessment by BI-RADS Categories.

Science.gov (United States)

Singh, Tulika; Sharma, Madhurima; Singla, Veenu; Khandelwal, Niranjan

2016-01-01

The objective of our study was to calculate mammographic breast density with a fully automated volumetric breast density measurement method and to compare it to breast imaging reporting and data system (BI-RADS) breast density categories assigned by two radiologists. A total of 476 full-field digital mammography examinations with standard mediolateral oblique and craniocaudal views were evaluated by two blinded radiologists and BI-RADS density categories were assigned. Using a fully automated software, mean fibroglandular tissue volume, mean breast volume, and mean volumetric breast density were calculated. Based on percentage volumetric breast density, a volumetric density grade was assigned from 1 to 4. The weighted overall kappa was 0.895 (almost perfect agreement) for the two radiologists' BI-RADS density estimates. A statistically significant difference was seen in mean volumetric breast density among the BI-RADS density categories. With increased BI-RADS density category, increase in mean volumetric breast density was also seen (P BI-RADS categories and volumetric density grading by fully automated software (ρ = 0.728, P BI-RADS density category by two observers showed fair agreement (κ = 0.398 and 0.388, respectively). In our study, a good correlation was seen between density grading using fully automated volumetric method and density grading using BI-RADS density categories assigned by the two radiologists. Thus, the fully automated volumetric method may be used to quantify breast density on routine mammography. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Development and clinical evaluation of automatic fiducial detection for tumor tracking in cine megavoltage images during volumetric modulated arc therapy

International Nuclear Information System (INIS)

Azcona, Juan Diego; Li Ruijiang; Mok, Edward; Hancock, Steven; Xing Lei

2013-01-01

Purpose: Real-time tracking of implanted fiducials in cine megavoltage (MV) imaging during volumetric modulated arc therapy (VMAT) delivery is complicated due to the inherent low contrast of MV images and potential blockage of dynamic leaves configurations. The purpose of this work is to develop a clinically practical autodetection algorithm for motion management during VMAT. Methods: The expected field-specific segments and the planned fiducial position from the Eclipse (Varian Medical Systems, Palo Alto, CA) treatment planning system were projected onto the MV images. The fiducials were enhanced by applying a Laplacian of Gaussian filter in the spatial domain for each image, with a blob-shaped object as the impulse response. The search of implanted fiducials was then performed on a region of interest centered on the projection of the fiducial when it was within an open field including the case when it was close to the field edge or partially occluded by the leaves. A universal template formula was proposed for template matching and normalized cross correlation was employed for its simplicity and computational efficiency. The search region for every image was adaptively updated through a prediction model that employed the 3D position of the fiducial estimated from the localized positions in previous images. This prediction model allowed the actual fiducial position to be tracked dynamically and was used to initialize the search region. The artifacts caused by electronic interference during the acquisition were effectively removed. A score map was computed by combining both morphological information and image intensity. The pixel location with the highest score was selected as the detected fiducial position. The sets of cine MV images taken during treatment were analyzed with in-house developed software written in MATLAB (The Mathworks, Inc., Natick, MA). Five prostate patients were analyzed to assess the algorithm performance by measuring their positioning

Erosion of water-based cements evaluated by volumetric and gravimetric methods.

Science.gov (United States)

Nomoto, Rie; Uchida, Keiko; Momoi, Yasuko; McCabe, John F

2003-05-01

To compare the erosion of glass ionomer, zinc phosphate and polycarboxylate cements using volumetric and gravimetric methods. For the volumetric method, the eroded depth of cement placed in a cylindrical cavity in PMMA was measured using a dial gauge after immersion in an eroding solution. For the gravimetric method, the weight of the residue of a solution in which a cylindrical specimen had been immersed was measured. 0.02 M lactic acid solution (0.02 M acid) and 0.1 M lactic acid/sodium lactate buffer solution (0.1 M buffer) were used as eroding solutions. The pH of both solutions was 2.74 and the test period was 24 h. Ranking of eroded depth and weight of residue was polycarboxylate>zinc phosphate>glass ionomers. Differences in erosion were more clearly defined by differences in eroded depth than differences in weight of residue. In 0.02 M acid, the erosion of glass ionomer using the volumetric method was effected by the hygroscopic expansion. In 0.1 M buffer, the erosion for polycarboxylate and zinc phosphate using the volumetric method was much greater than that using the gravimetric method. This is explained by cryo-SEM images which show many holes in the surface of specimens after erosion. It appears that zinc oxide is dissolved leaving a spongy matrix which easily collapses under the force applied to the dial gauge during measurement. The volumetric method that employs eroded depth of cement using a 0.1 M buffer solution is able to quantify erosion and to make material comparisons.

MEDICAL IMAGE COMPRESSION USING HYBRID CODER WITH FUZZY EDGE DETECTION

Directory of Open Access Journals (Sweden)

K. Vidhya

2011-02-01

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

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)

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.