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Journal of Medical Imaging

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https://www.readbyqxmd.com/read/28331891/differentiation-of-arterioles-from-venules-in-mouse-histology-images-using-machine-learning
#1
J Sachi Elkerton, Yiwen Xu, J Geoffrey Pickering, Aaron D Ward
Analysis and morphological comparison of the arteriolar and venular components of a microvascular network are essential to our understanding of multiple diseases affecting every organ system. We have developed and evaluated the first fully automatic software system for differentiation of arterioles from venules on high-resolution digital histology images of the mouse hind limb immunostained with smooth muscle [Formula: see text]-actin. Classifiers trained on statistical and morphological features by supervised machine learning provided useful classification accuracy for differentiation of arterioles from venules, achieving an area under the receiver operating characteristic curve of 0...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331890/predicting-and-replacing-the-pathological-gleason-grade-with-automated-gland-ring-morphometric-features-from-immunofluorescent-prostate-cancer-images
#2
Faisal M Khan, Richard Scott, Michael Donovan, Gerardo Fernandez
The Gleason grade is the most common architectural and morphological assessment of prostate cancer severity and prognosis. There have been numerous algorithms developed to approximate and duplicate the Gleason scoring system, mostly developed in standard H&E brightfield microscopy. Immunofluorescence (IF) image analysis of tissue pathology has recently been proven to be robust in developing prognostic assessments of disease, particularly in prostate cancer. We leverage a method of segmenting gland rings in IF images for predicting the pathological Gleason, both the clinical and the image specific grades, which may not necessarily be the same...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331889/unsupervised-labeling-of-glomerular-boundaries-using-gabor-filters-and-statistical-testing-in-renal-histology
#3
Brandon Ginley, John E Tomaszewski, Rabi Yacoub, Feng Chen, Pinaki Sarder
The glomerulus is the blood filtering unit of the kidney. Each human kidney contains [Formula: see text] glomeruli. Several renal conditions originate from structural damage to glomerular microcompartments, such as proteinuria, the excessive loss of blood proteins into urine. The gold standard for evaluating structural damage in renal pathology is histopathological and immunofluorescence examination of needle biopsies under a light microscope. This method is limited by qualitative or semiquantitative manual scoring approaches to the evaluation of glomerular structural features...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331888/new-concept-on-an-integrated-interior-magnetic-resonance-imaging-and-medical-linear-accelerator-system-for-radiation-therapy
#4
Xun Jia, Zhen Tian, Yan Xi, Steve B Jiang, Ge Wang
Image guidance plays a critical role in radiotherapy. Currently, cone-beam computed tomography (CBCT) is routinely used in clinics for this purpose. While this modality can provide an attenuation image for therapeutic planning, low soft-tissue contrast affects the delineation of anatomical and pathological features. Efforts have recently been devoted to several MRI linear accelerator (LINAC) projects that lead to the successful combination of a full diagnostic MRI scanner with a radiotherapy machine. We present a new concept for the development of the MRI-LINAC system...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331887/android-application-for-determining-surgical-variables-in-brain-tumor-resection-procedures
#5
Rohan C Vijayan, Reid C Thompson, Lola B Chambless, Peter J Morone, Le He, Logan W Clements, Rebekah H Griesenauer, Hakmook Kang, Michael I Miga
The fidelity of image-guided neurosurgical procedures is often compromised due to the mechanical deformations that occur during surgery. In recent work, a framework was developed to predict the extent of this brain shift in brain-tumor resection procedures. The approach uses preoperatively determined surgical variables to predict brain shift and then subsequently corrects the patient's preoperative image volume to more closely match the intraoperative state of the patient's brain. However, a clinical workflow difficulty with the execution of this framework is the preoperative acquisition of surgical variables...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331886/effects-of-line-fiducial-parameters-and-beamforming-on-ultrasound-calibration
#6
Golafsoun Ameri, John S H Baxter, A Jonathan McLeod, Terry M Peters, Elvis C S Chen
Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the total accuracy of the interventional guidance system. Here, we investigate the effects of US image reconstruction techniques as well as phantom material and geometry on US calibration...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331885/formulation-of-image-fusion-as-a-constrained-least-squares-optimization-problem
#7
Nicholas Dwork, Eric M Lasry, John M Pauly, Jorge Balbás
Fusing a lower resolution color image with a higher resolution monochrome image is a common practice in medical imaging. By incorporating spatial context and/or improving the signal-to-noise ratio, it provides clinicians with a single frame of the most complete information for diagnosis. In this paper, image fusion is formulated as a convex optimization problem that avoids image decomposition and permits operations at the pixel level. This results in a highly efficient and embarrassingly parallelizable algorithm based on widely available robust and simple numerical methods that realizes the fused image as the global minimizer of the convex optimization problem...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331884/accuracy-assessment-and-characterization-of-x-ray-coded-aperture-coherent-scatter-spectral-imaging-for-breast-cancer-classification
#8
Manu N Lakshmanan, Joel A Greenberg, Ehsan Samei, Anuj J Kapadia
Although transmission-based x-ray imaging is the most commonly used imaging approach for breast cancer detection, it exhibits false negative rates higher than 15%. To improve cancer detection accuracy, x-ray coherent scatter computed tomography (CSCT) has been explored to potentially detect cancer with greater consistency. However, the 10-min scan duration of CSCT limits its possible clinical applications. The coded aperture coherent scatter spectral imaging (CACSSI) technique has been shown to reduce scan time through enabling single-angle imaging while providing high detection accuracy...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28331883/practical-no-gold-standard-evaluation-framework-for-quantitative-imaging-methods-application-to-lesion-segmentation-in-positron-emission-tomography
#9
Abhinav K Jha, Esther Mena, Brian Caffo, Saeed Ashrafinia, Arman Rahmim, Eric Frey, Rathan M Subramaniam
Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28217714/dr-hagis-a-fundus-image-database-for-the-automatic-extraction-of-retinal-surface-vessels-from-diabetic-patients
#10
Sven Holm, Greg Russell, Vincent Nourrit, Niall McLoughlin
A database of retinal fundus images, the DR HAGIS database, is presented. This database consists of 39 high-resolution color fundus images obtained from a diabetic retinopathy screening program in the UK. The NHS screening program uses service providers that employ different fundus and digital cameras. This results in a range of different image sizes and resolutions. Furthermore, patients enrolled in such programs often display other comorbidities in addition to diabetes. Therefore, in an effort to replicate the normal range of images examined by grading experts during screening, the DR HAGIS database consists of images of varying image sizes and resolutions and four comorbidity subgroups: collectively defined as the diabetic retinopathy, hypertension, age-related macular degeneration, and Glaucoma image set (DR HAGIS)...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28180134/quantitative-assessment-of-soft-tissue-deformation-using-digital-speckle-pattern-interferometry-studies-on-phantom-breast-models
#11
Udayakumar Karuppanan, Sujatha Narayanan Unni, Ganesan R Angarai
Assessment of mechanical properties of soft matter is a challenging task in a purely noninvasive and noncontact environment. As tissue mechanical properties play a vital role in determining tissue health status, such noninvasive methods offer great potential in framing large-scale medical screening strategies. The digital speckle pattern interferometry (DSPI)-based image capture and analysis system described here is capable of extracting the deformation information from a single acquired fringe pattern. Such a method of analysis would be required in the case of the highly dynamic nature of speckle patterns derived from soft tissues while applying mechanical compression...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28180133/patch-based-denoising-method-using-low-rank-technique-and-targeted-database-for-optical-coherence-tomography-image
#12
Xiaoming Liu, Zhou Yang, Jia Wang, Jun Liu, Kai Zhang, Wei Hu
Image denoising is a crucial step before performing segmentation or feature extraction on an image, which affects the final result in image processing. In recent years, utilizing the self-similarity characteristics of the images, many patch-based image denoising methods have been proposed, but most of them, named the internal denoising methods, utilized the noisy image only where the performances are constrained by the limited information they used. We proposed a patch-based method, which uses a low-rank technique and targeted database, to denoise the optical coherence tomography (OCT) image...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28180132/study-of-material-properties-important-for-an-optical-property-modulation-based-radiation-detection-method-for-positron-emission-tomography
#13
Li Tao, Henry M Daghighian, Craig S Levin
We compare the performance of two detector materials, cadmium telluride (CdTe) and bismuth silicon oxide (BSO), for optical property modulation-based radiation detection method for positron emission tomography (PET), which is a potential new direction to dramatically improve the annihilation photon pair coincidence time resolution. We have shown that the induced current flow in the detector crystal resulting from ionizing radiation determines the strength of optical modulation signal. A larger resistivity is favorable for reducing the dark current (noise) in the detector crystal, and thus the higher resistivity BSO crystal has a lower (50% lower on average) noise level than CdTe...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149926/tissue-classification-for-laparoscopic-image-understanding-based-on-multispectral-texture-analysis
#14
Yan Zhang, Sebastian J Wirkert, Justin Iszatt, Hannes Kenngott, Martin Wagner, Benjamin Mayer, Christian Stock, Neil T Clancy, Daniel S Elson, Lena Maier-Hein
Intraoperative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study through statistical analysis, we show that (1) multispectral imaging data are superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) combining the tissue texture with the reflectance spectrum improves the classification performance...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149925/automated-detection-of-coarctation-of-aorta-in-neonates-from-two-dimensional-echocardiograms
#15
Franklin Pereira, Alejandra Bueno, Andrea Rodriguez, Douglas Perrin, Gerald Marx, Michael Cardinale, Ivan Salgo, Pedro Del Nido
Coarctation of aorta (CoA) is a critical congenital heart defect (CCHD) that requires accurate and immediate diagnosis and treatment. Current newborn screening methods to detect CoA lack both in sensitivity and specificity, and when suspected in a newborn, it must be confirmed using specialized imaging and expert diagnosis, both of which are usually unavailable at tertiary birthing centers. We explore the feasibility of applying machine learning methods to reliably determine the presence of this difficult-to-diagnose cardiac abnormality from ultrasound image data...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149924/deformable-image-registration-for-tissues-with-large-displacements
#16
Xishi Huang, Jing Ren, Anwar Abdalbari, Mark Green
Image registration for internal organs and soft tissues is considered extremely challenging due to organ shifts and tissue deformation caused by patients' movements such as respiration and repositioning. In our previous work, we proposed a fast registration method for deformable tissues with small rotations. We extend our method to deformable registration of soft tissues with large displacements. We analyzed the deformation field of the liver by decomposing the deformation into shift, rotation, and pure deformation components and concluded that in many clinical cases, the liver deformation contains large rotations and small deformations...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149923/investigation-of-x-ray-spectra-for-iodinated-contrast-enhanced-dedicated-breast-ct
#17
Stephen J Glick, Andrey Makeev
Screening for breast cancer with mammography has been very successful, resulting in part to a reduction of breast cancer mortality by approximately 39% since 1990. However, mammography still has limitations in performance, especially for women with dense breast tissue. Iodinated contrast-enhanced, dedicated breast CT (BCT) has been proposed to improve lesion analysis and the accuracy of diagnostic workup for patients suspected of having breast cancer. A mathematical analysis to explore the use of various x-ray filters for iodinated contrast-enhanced BCT is presented...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149922/automated-patient-specific-estimation-of-regional-imparted-energy-and-dose-from-tube-current-modulated-computed-tomography-exams-across-13-protocols
#18
Jeremiah Sanders, Xiaoyu Tian, William Paul Segars, John Boone, Ehsan Samei
Currently, computed tomography (CT) dosimetry relies on surrogates for dose, such as CT dose index and size-specific dose estimates, rather than dose per se. Organ dose is considered as the gold standard for radiation dosimetry. However, organ dose estimation requires precise knowledge of organ locations. Regional imparted energy and dose can also be used to quantify radiation burden and are beneficial because they do not require knowledge of organ size or location. This work investigated an automated technique to retrospectively estimate the imparted energy from tube current-modulated (TCM) CT exams across 13 protocols...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149921/mean-glandular-dose-in-digital-mammography-a-dose-calculation-method-comparison
#19
Moayyad E Suleiman, Patrick C Brennan, Mark F McEntee
Our objective was to analyze the agreement between organ dose estimated by different digital mammography units and calculated dose for clinical data. Digital Imaging and Communication in Medicine header information was extracted from 52,405 anonymized mammograms. Data were filtered to include images with no breast implants, breast thicknesses 20 to 110 mm, and complete exposure and quality assurance data. Mean glandular dose was calculated using methods by Dance et al., Wu et al., and Boone et al. Bland-Altman analysis and regression were used to study the agreement and correlation between organ and calculated doses...
January 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28149920/hybrid-positron-emission-tomography-segmentation-of-heterogeneous-lung-tumors-using-3d-slicer-improved-growcut-algorithm-with-threshold-initialization
#20
Hannah Mary T Thomas, Devadhas Devakumar, Balukrishna Sasidharan, Stephen R Bowen, Danie Kingslin Heck, E James Jebaseelan Samuel
This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a three-dimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm...
January 2017: Journal of Medical Imaging
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