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Journal of Medical Imaging

Jessica Kishimoto, Sandrine de Ribaupierre, Fateme Salehi, Walter Romano, David S C Lee, Aaron Fenster
The aim of this study is to compare longitudinal two-dimensional (2-D) and three-dimensional (3-D) ultrasound (US) estimates of ventricle size in preterm neonates with posthemorrhagic ventricular dilatation (PHVD) using quantitative measurements of the lateral ventricles. Cranial 2-D US and 3-D US images were acquired from neonatal patients with diagnosed PHVD within 10 min of each other one to two times per week and analyzed offline. Ventricle index, anterior horn width, third ventricle width, and thalamo-occipital distance were measured on the 2-D images and ventricle volume (VV) was measured from 3-D US images...
October 2016: Journal of Medical Imaging
Maysam Shahedi, Derek W Cool, Cesare Romagnoli, Glenn S Bauman, Matthew Bastian-Jordan, George Rodrigues, Belal Ahmad, Michael Lock, Aaron Fenster, Aaron D Ward
Prostate segmentation on T2w MRI is important for several diagnostic and therapeutic procedures for prostate cancer. Manual segmentation is time-consuming, labor-intensive, and subject to high interobserver variability. This study investigated the suitability of computer-assisted segmentation algorithms for clinical translation, based on measurements of interoperator variability and measurements of the editing time required to yield clinically acceptable segmentations. A multioperator pilot study was performed under three pre- and postediting conditions: manual, semiautomatic, and automatic segmentation...
October 2016: Journal of Medical Imaging
Nicholas Tran, Archontis Giannakidis, Grant T Gullberg, Youngho Seo
Systemic hypertension is a causative factor in left ventricular hypertrophy (LVH). This study is motivated by the potential to reverse or manage the dysfunction associated with structural remodeling of the myocardium in this pathology. Using diffusion tensor magnetic resonance imaging, we present an analysis of myocardial fiber and laminar sheet orientation in ex vivo hypertrophic (6 SHR) and normal (5 WKY) rat hearts using the covariance of the diffusion tensor. First, an atlas of normal cardiac microstructure was formed using the WKY b0 images...
October 2016: Journal of Medical Imaging
Hadi Rezaeilouyeh, Ali Mollahosseini, Mohammad H Mahoor
Cancer is the second leading cause of death in US after cardiovascular disease. Image-based computer-aided diagnosis can assist physicians to efficiently diagnose cancers in early stages. Existing computer-aided algorithms use hand-crafted features such as wavelet coefficients, co-occurrence matrix features, and recently, histogram of shearlet coefficients for classification of cancerous tissues and cells in images. These hand-crafted features often lack generalizability since every cancerous tissue and cell has a specific texture, structure, and shape...
October 2016: Journal of Medical Imaging
Xuejin Liu, Mats Persson, Hans Bornefalk, Staffan Karlsson, Cheng Xu, Mats Danielsson, Ben Huber
[This corrects the article DOI: 10.1117/1.JMI.2.3.033502.].
October 2016: Journal of Medical Imaging
Patrick Leo, George Lee, Natalie N C Shih, Robin Elliott, Michael D Feldman, Anant Madabhushi
Quantitative histomorphometry (QH) is the process of computerized feature extraction from digitized tissue slide images to predict disease presence, behavior, and outcome. Feature stability between sites may be compromised by laboratory-specific variables including dye batch, slice thickness, and the whole slide scanner used. We present two new measures, preparation-induced instability score and latent instability score, to quantify feature instability across and within datasets. In a use case involving prostate cancer, we examined QH features which may detect cancer on whole slide images...
October 2016: Journal of Medical Imaging
Rushin Shojaii, Anne L Martel
The registration of two-dimensional histology images to reference images from other modalities is an important preprocessing step in the reconstruction of three-dimensional histology volumes. This is a challenging problem because of the differences in the appearances of histology images and other modalities, and the presence of large nonrigid deformations which occur during slide preparation. This paper shows the feasibility of using densely sampled scale-invariant feature transform (SIFT) features and a SIFTFlow deformable registration algorithm for coregistering whole-mount histology images with blockface optical images...
October 2016: Journal of Medical Imaging
Xinyang Liu, Sukryool Kang, William Plishker, George Zaki, Timothy D Kane, Raj Shekhar
The purpose of this work was to develop a clinically viable laparoscopic augmented reality (AR) system employing stereoscopic (3-D) vision, laparoscopic ultrasound (LUS), and electromagnetic (EM) tracking to achieve image registration. We investigated clinically feasible solutions to mount the EM sensors on the 3-D laparoscope and the LUS probe. This led to a solution of integrating an externally attached EM sensor near the imaging tip of the LUS probe, only slightly increasing the overall diameter of the probe...
October 2016: Journal of Medical Imaging
Tomoka Ueno, Yasushi Shimada, Khairul Matin, Yuan Zhou, Ikumi Wada, Alireza Sadr, Yasunori Sumi, Junji Tagami
The aim of this study was to evaluate the signal intensity and signal attenuation of swept source optical coherence tomography (SS-OCT) for dental caries in relation to the variation of mineral density. SS-OCT observation was performed on the enamel and dentin artificial demineralization and on natural caries. The artificial caries model on enamel and dentin surfaces was created using Streptococcus mutans biofilms incubated in an oral biofilm reactor. The lesions were centrally cross sectioned and SS-OCT scans were obtained in two directions to construct a three-dimensional data set, from the lesion surface (sagittal scan) and parallel to the lesion surface (horizontal scan)...
July 2016: Journal of Medical Imaging
Justin Solomon, Ehsan Samei
The purpose of this study was to compare computed tomography (CT) low-contrast detectability from human readers with observer model-based surrogates of image quality. A phantom with a range of low-contrast signals (five contrasts, three sizes) was imaged on a state-of-the-art CT scanner (Siemens' force). Images were reconstructed using filtered back projection and advanced modeled iterative reconstruction and were assessed by 11 readers using a two alternative forced choice method. Concurrently, contrast-to-noise ratio (CNR), area-weighted CNR (CNRA), and observer model-based metrics were estimated, including nonprewhitening (NPW) matched filter, NPW with eye filter (NPWE), NPW with internal noise, NPW with an eye filter and internal noise (NPWEi), channelized Hotelling observer (CHO), and CHO with internal noise (CHOi)...
July 2016: Journal of Medical Imaging
Yiyuan Zhao, Benoit M Dawant, Jack H Noble
Cochlear implants (CIs) are neural prostheses that restore hearing by stimulating auditory nerve pathways within the cochlea using an implanted electrode array. Research has shown when multiple electrodes stimulate the same nerve pathways, competing stimulation occurs and hearing outcomes decline. Recent clinical studies have indicated that hearing outcomes can be significantly improved by using an image-guided active electrode set selection technique we have designed, in which electrodes that cause competing stimulation are identified and deactivated...
July 2016: Journal of Medical Imaging
Claudia I Henschke, David F Yankelevitz, Rowena Yip, Venice Archer, Gudrun Zahlmann, Karthik Krishnan, Brian Helba, Ricardo Avila
To address the error introduced by computed tomography (CT) scanners when assessing volume and unidimensional measurement of solid tumors, we scanned a precision manufactured pocket phantom simultaneously with patients enrolled in a lung cancer clinical trial. Dedicated software quantified bias and random error in the [Formula: see text], and [Formula: see text] dimensions of a Teflon sphere and also quantified response evaluation criteria in solid tumors and volume measurements using both constant and adaptive thresholding...
July 2016: Journal of Medical Imaging
Nooshin Kiarashi, Loren W Nolte, Joseph Y Lo, W Paul Segars, Sujata V Ghate, Justin B Solomon, Ehsan Samei
This study aims to characterize the effect of background tissue density and heterogeneity on the detection of irregular masses in breast tomosynthesis, while demonstrating the capability of the sophisticated tools that can be used in the design, implementation, and performance analysis of virtual clinical trials (VCTs). Twenty breast phantoms from the extended cardiac-torso (XCAT) family, generated based on dedicated breast computed tomography of human subjects, were used to extract a total of 2173 volumes of interest (VOIs) from simulated tomosynthesis images...
July 2016: Journal of Medical Imaging
Jing Wu, Mohamed R Mahfouz
Extraction of bone contours from x-ray radiographs plays an important role in joint space width assessment, preoperative planning, and kinematics analysis. We present a robust segmentation method to accurately extract the distal femur and proximal tibia in knee radiographs of varying image quality. A spectral clustering method based on the eigensolution of an affinity matrix is utilized for x-ray image denoising. An active shape model-based segmentation method is employed for robust and accurate segmentation of the denoised x-ray images...
July 2016: Journal of Medical Imaging
Mahsa Paknezhad, Stephanie Marchesseau, Michael S Brown
Identification of the basal slice in cardiac imaging is a key step to measuring the ejection fraction of the left ventricle. Despite all the effort placed on automatic cardiac segmentation, basal slice identification is routinely performed manually. Manual identification, however, suffers from high interobserver variability. As a result, an automatic algorithm for basal slice identification is required. Guidelines published in 2013 identify the basal slice based on the percentage of myocardium surrounding the blood cavity in the short-axis view...
July 2016: Journal of Medical Imaging
Alexander Norlén, Jennifer Alvén, David Molnar, Olof Enqvist, Rauni Rossi Norrlund, John Brandberg, Göran Bergström, Fredrik Kahl
Recent findings indicate a strong correlation between the risk of future heart disease and the volume of adipose tissue inside of the pericardium. So far, large-scale studies have been hindered by the fact that manual delineation of the pericardium is extremely time-consuming and that existing methods for automatic delineation lack accuracy. An efficient and fully automatic approach to pericardium segmentation and epicardial fat volume (EFV) estimation is presented, based on a variant of multi-atlas segmentation for spatial initialization and a random forest classifier for accurate pericardium detection...
July 2016: Journal of Medical Imaging
Sinan Onal, Xin Chen, Veeresh Satamraju, Maduka Balasooriya, Humeyra Dabil-Karacal
Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space...
July 2016: Journal of Medical Imaging
Zhoubing Xu, Benjamin N Conrad, Rebeccah B Baucom, Seth A Smith, Benjamin K Poulose, Bennett A Landman
Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework...
July 2016: Journal of Medical Imaging
Benjamin Q Huynh, Hui Li, Maryellen L Giger
Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images)...
July 2016: Journal of Medical Imaging
Emily Huynh, Danuta M Bukowska, Seyhan Yazar, Charlotte M McKnight, Ajmal Mian, David A Mackey
Quantification of sun-related changes in conjunctival ultraviolet autofluorescence (CUVAF) images is a subjective and tedious task, in which reproducibility of results is difficult. Thus, we have developed a semiautomatic method in MATLAB(®) to analyze CUVAF images retrospectively. The algorithm was validated on 200 images from 50 randomly selected participants from the Western Australian Pregnancy Cohort (Raine) study 20-year follow-up assessment, in which CUVAF area measurements were available from previous manual analysis...
July 2016: Journal of Medical Imaging
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