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Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society

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https://www.readbyqxmd.com/read/28087102/feature-selection-for-outcome-prediction-in-oesophageal-cancer-using-genetic-algorithm-and-random-forest-classifier
#1
Desbordes Paul, Ruan Su, Modzelewski Romain, Vauclin Sébastien, Vera Pierre, Gardin Isabelle
The outcome prediction of patients can greatly help to personalize cancer treatment. A large amount of quantitative features (clinical exams, imaging, …) are potentially useful to assess the patient outcome. The challenge is to choose the most predictive subset of features. In this paper, we propose a new feature selection strategy called GARF (genetic algorithm based on random forest) extracted from positron emission tomography (PET) images and clinical data. The most relevant features, predictive of the therapeutic response or which are prognoses of the patient survival 3 years after the end of treatment, were selected using GARF on a cohort of 65 patients with a local advanced oesophageal cancer eligible for chemo-radiation therapy...
December 28, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27955798/automatic-detection-and-classification-of-regions-of-fdg-uptake-in-whole-body-pet-ct-lymphoma-studies
#2
Lei Bi, Jinman Kim, Ashnil Kumar, Lingfeng Wen, Dagan Feng, Michael Fulham
[(18)F]-Fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-CT) scans of lymphoma patients usually show disease involvement as foci of increased radiotracer uptake. Existing methods for detecting abnormalities, model the characteristics of these foci; this is challenging due to the inconsistent shape and localization information about the lesions. Thresholding the degree of FDG uptake is the standard method to separate different sites of involvement. But may fragment sites into smaller regions, and may also incorrectly identify sites of normal physiological FDG uptake and normal FDG excretion (sFEPU) such as the kidneys, bladder, brain and heart...
December 2, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27914956/individual-refinement-of-attenuation-correction-maps-for-hybrid-pet-mr-based-on-multi-resolution-regional-learning
#3
Kuangyu Shi, Sebastian Fürst, Liang Sun, Mathias Lukas, Nassir Navab, Stefan Förster, Sibylle I Ziegler
PET/MR is an emerging hybrid imaging modality. However, attenuation correction (AC) remains challenging for hybrid PET/MR in generating accurate PET images. Segmentation-based methods on special MR sequences are most widely recommended by vendors. However, their accuracy is usually not high. Individual refinement of available certified attenuation maps may be helpful for further clinical applications. In this study, we proposed a multi-resolution regional learning (MRRL) scheme to utilize the internal consistency of the patient data...
November 19, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/28062170/an-artificial-neural-network-method-for-lumen-and-media-adventitia-border-detection-in-ivus
#4
Shengran Su, Zhenghui Hu, Qiang Lin, William Kongto Hau, Zhifan Gao, Heye Zhang
Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to determine the plaque burden inside the coronary arteries, but this detection could be burdensome to the doctor because of large volume of the IVUS images. In this paper, we use the artificial neural network (ANN) method as the feature learning algorithm for the detection of the lumen and MA borders in IVUS images...
November 17, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27939282/a-minimally-interactive-and-reproducible-method-for-abdominal-aortic-aneurysm-quantification-in-3d-ultrasound-and-computed-tomography-with-implicit-template-deformations
#5
L Rouet, B Mory, E Attia, K Bredahl, A Long, R Ardon
The maximum diameter of abdominal aortic aneurysm (AAA) is a key quantification parameter for disease assessment. Although it is routinely measured on 2D-ultrasound images, using a volumetric approach is expected to improve measurement reproducibility. In this work, 3D-ultrasound or computed tomography imaging of patients with AAA was combined with a minimally interactive 3D segmentation based on implicit template deformation. Segmentation usability and reproducibility were evaluated on 81 patients, showing a mean measurement time of [2;8]min per case, and Dice coefficients of 0...
November 16, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27887989/quantitative-pet-image-reconstruction-employing-nested-expectation-maximization-deconvolution-for-motion-compensation
#6
Nicolas A Karakatsanis, Charalampos Tsoumpas, Habib Zaidi
Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources...
November 16, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27876173/automated-detection-of-bone-metastatic-changes-using-serial-ct-scans
#7
Jihun Oh, Gyehyun Kim, Jaesung Lee, Minsu Cheon, Yongsup Park, Sewon Kim, Jonghyon Yi, Ho Yun Lee
Bone metastases resulting from a primary tumor invasion to the bone are common and cause significant morbidity in advanced cancer patients. Although the detection of bone metastases is often straightforward, it is difficult to identify their spread and track their changes, particularly in early stages. This paper presents a novel method that automatically finds the changes in appearance and the progress of bone metastases using longitudinal CT images. In contrast to previous methods based on nodule detection within a specific bone site in an individual CT scan, the approach in the present study is based on the subtraction between two registered CT volumes...
November 13, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27986379/lung-nodule-classification-using-deep-feature-fusion-in-chest-radiography
#8
Changmiao Wang, Ahmed Elazab, Jianhuang Wu, Qingmao Hu
Lung nodules are small, round, or oval-shaped masses of tissue in the lung region. Early diagnosis and treatment of lung nodules can significantly improve the quality of patients' lives. Because of their small size and the interlaced nature of chest anatomy, detection of lung nodules using different medical imaging techniques becomes challenging. Recently, several methods for computer aided diagnosis (CAD) were proposed to improve the detection of lung nodules with good performances. However, the current methods are unable to achieve high sensitivity and high specificity...
November 12, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27887990/withdrawn-the-new-approach-of-multiple-genome-sequence-parallel-matching-based-on-gpu
#9
Sha Ding, Shi-Yuan Zhao, Gang Liao, Tao Lin
This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.
November 11, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/28063502/preface
#10
EDITORIAL
Xinjian Chen, Shuo Li, Emanuele Trucco, Jimmy Jiang Liu, Yonggang Shi, Beiji Zou
No abstract text is available yet for this article.
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27665058/a-location-to-segmentation-strategy-for-automatic-exudate-segmentation-in-colour-retinal-fundus-images
#11
Qing Liu, Beiji Zou, Jie Chen, Wei Ke, Kejuan Yue, Zailiang Chen, Guoying Zhao
The automatic exudate segmentation in colour retinal fundus images is an important task in computer aided diagnosis and screening systems for diabetic retinopathy. In this paper, we present a location-to-segmentation strategy for automatic exudate segmentation in colour retinal fundus images, which includes three stages: anatomic structure removal, exudate location and exudate segmentation. In anatomic structure removal stage, matched filters based main vessels segmentation method and a saliency based optic disk segmentation method are proposed...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27634547/local-characterization-of-neovascularization-and-identification-of-proliferative-diabetic-retinopathy-in-retinal-fundus-images
#12
Garima Gupta, S Kulasekaran, Keerthi Ram, Niranjan Joshi, Mohanasankar Sivaprakasam, Rashmin Gandhi
Neovascularization (NV) is a characteristic of the onset of sight-threatening stage of DR, called proliferative DR (PDR). Identification of PDR requires modeling of these unregulated ill-formed vessels, and other associated signs of PDR. We present an approach that models the micro-pattern of local variations (using texture based analysis) and quantifies structural changes in vessel patterns in localized patches, to arrive at a score of neovascularity. The distribution of patch-level confidence scores is collated into an image-level decision of presence or absence of PDR...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27614678/automated-layer-segmentation-of-macular-oct-images-via-graph-based-slic-superpixels-and-manifold-ranking-approach
#13
Zhijun Gao, Wei Bu, Yalin Zheng, Xiangqian Wu
Using the graph-based a simple linear iterative clustering (SLIC) superpixels and manifold ranking technology, a novel automated intra-retinal layer segmentation method is proposed in this paper. Eleven boundaries of ten retinal layers in optical coherence tomography (OCT) images are exactly, fast and reliably quantified. Instead of considering the intensity or gradient features of the single-pixel in most existing segmentation methods, the proposed method focuses on the superpixels and the connected components-based image cues...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27595214/automatic-detection-of-microaneurysms-in-retinal-fundus-images
#14
Bo Wu, Weifang Zhu, Fei Shi, Shuxia Zhu, Xinjian Chen
Diabetic retinopathy (DR) is one of the leading causes of new cases of blindness. Early and accurate detection of microaneurysms (MAs) is important for diagnosis and grading of diabetic retinopathy. In this paper, a new method for the automatic detection of MAs in eye fundus images is proposed. The proposed method consists of four main steps: preprocessing, candidate extraction, feature extraction and classification. A total of 27 characteristic features which contain local features and profile features are extracted for KNN classifier to distinguish true MAs from spurious candidates...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27590198/glaucoma-detection-using-entropy-sampling-and-ensemble-learning-for-automatic-optic-cup-and-disc-segmentation
#15
Julian Zilly, Joachim M Buhmann, Dwarikanath Mahapatra
We present a novel method to segment retinal images using ensemble learning based convolutional neural network (CNN) architectures. An entropy sampling technique is used to select informative points thus reducing computational complexity while performing superior to uniform sampling. The sampled points are used to design a novel learning framework for convolutional filters based on boosting. Filters are learned in several layers with the output of previous layers serving as the input to the next layer. A softmax logistic classifier is subsequently trained on the output of all learned filters and applied on test images...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27553657/influence-of-applied-corneal-endothelium-image-segmentation-techniques-on-the-clinical-parameters
#16
Adam Piorkowski, Karolina Nurzynska, Jolanta Gronkowska-Serafin, Bettina Selig, Cezary Boldak, Daniel Reska
The corneal endothelium state is verified on the basis of an in vivo specular microscope image from which the shape and density of cells are exploited for data description. Due to the relatively low image quality resulting from a high magnification of the living, non-stained tissue, both manual and automatic analysis of the data is a challenging task. Although, many automatic or semi-automatic solutions have already been introduced, all of them are prone to inaccuracy. This work presents a comparison of four methods (fully-automated or semi-automated) for endothelial cell segmentation, all of which represent a different approach to cell segmentation; fast robust stochastic watershed (FRSW), KH method, active contours solution (SNAKE), and TOPCON ImageNET...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27515743/performance-comparison-of-publicly-available-retinal-blood-vessel-segmentation-methods
#17
Pavel Vostatek, Ela Claridge, Hannu Uusitalo, Markku Hauta-Kasari, Pauli Fält, Lasse Lensu
Retinal blood vessel structure is an important indicator of many retinal and systemic diseases, which has motivated the development of various image segmentation methods for the blood vessels. In this study, two supervised and three unsupervised segmentation methods with a publicly available implementation are reviewed and quantitatively compared with each other on five public databases with ground truth segmentation of the vessels. Each method is tested under consistent conditions with two types of preprocessing, and the parameters of the methods are optimized for each database...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27507326/volumetric-image-classification-using-homogeneous-decomposition-and-dictionary-learning-a-study-using-retinal-optical-coherence-tomography-for-detecting-age-related-macular-degeneration
#18
Abdulrahman Albarrak, Frans Coenen, Yalin Zheng
Three-dimensional (3D) (volumetric) diagnostic imaging techniques are indispensable with respect to the diagnosis and management of many medical conditions. However there is a lack of automated diagnosis techniques to facilitate such 3D image analysis (although some support tools do exist). This paper proposes a novel framework for volumetric medical image classification founded on homogeneous decomposition and dictionary learning. In the proposed framework each image (volume) is recursively decomposed until homogeneous regions are arrived at...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27507325/incorporation-of-gradient-vector-flow-field-in-a-multimodal-graph-theoretic-approach-for-segmenting-the-internal-limiting-membrane-from-glaucomatous-optic-nerve-head-centered-sd-oct-volumes
#19
Mohammad Saleh Miri, Victor A Robles, Michael D Abràmoff, Young H Kwon, Mona K Garvin
The internal limiting membrane (ILM) separates the retina and optic nerve head (ONH) from the vitreous. In the optical coherence tomography volumes of glaucoma patients, while current approaches for the segmentation of the ILM in the peripapillary and macular regions are considered robust, current approaches commonly produce ILM segmentation errors at the ONH due to the presence of blood vessels and/or characteristic glaucomatous deep cupping. Because a precise segmentation of the ILM surface at the ONH is required for computing several newer structural measurements including Bruch's membrane opening-minimum rim width (BMO-MRW) and cup volume, in this study, we propose a multimodal multiresolution graph-based method to precisely segment the ILM surface within ONH-centered spectral-domain optical coherence tomography (SD-OCT) volumes...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/27507324/ensemble-based-adaptive-over-sampling-method-for-imbalanced-data-learning-in-computer-aided-detection-of-microaneurysm
#20
Fulong Ren, Peng Cao, Wei Li, Dazhe Zhao, Osmar Zaiane
Diabetic retinopathy (DR) is a progressive disease, and its detection at an early stage is crucial for saving a patient's vision. An automated screening system for DR can help in reduce the chances of complete blindness due to DR along with lowering the work load on ophthalmologists. Among the earliest signs of DR are microaneurysms (MAs). However, current schemes for MA detection appear to report many false positives because detection algorithms have high sensitivity. Inevitably some non-MAs structures are labeled as MAs in the initial MAs identification step...
January 2017: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
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