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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/30219737/case-control-comparison-brain-lesion-segmentation-for-early-infarct-detection
#1
Fung Fung Ting, Kok Swee Sim, Chee Peng Lim
Computed Tomography (CT) images are widely used for the identification of abnormal brain tissues following infarct and hemorrhage of a stroke. The treatment of this medical condition mainly depends on doctors' experience. While manual lesion delineation by medical doctors is currently considered as the standard approach, it is time-consuming and dependent on each doctor's expertise and experience. In this study, a case-control comparison brain lesion segmentation (CCBLS) method is proposed to segment the region pertaining to brain injury by comparing the voxel intensity of CT images between control subjects and stroke patients...
September 3, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30212736/a-wavelet-gradient-sparsity-based-algorithm-for-reconstruction-of-reduced-view-tomography-datasets-obtained-with-a-monochromatic-synchrotron-based-x-ray-source
#2
S Ali Melli, Khan A Wahid, Paul Babyn, David M L Cooper, Ahmed M Hasan
High-resolution synchrotron computed tomography (CT) is very helpful in the diagnosis and monitor of chronic diseases including osteoporosis. Osteoporosis is characterized by low bone mass and cortical bone porosity best imaged with CT. Synchrotron CT requires a large number of angular projections to reconstruct images with high resolution for detailed and accurate diagnosis. However, this poses great risks and challenges for serial in-vivo human and animal imaging due to a large amount of X-ray radiation dose required that can damage living specimens...
September 1, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30176518/learning-to-combine-complementary-segmentation-methods-for-fetal-and-6-month-infant-brain-mri-segmentation
#3
Gerard Sanroma, Oualid M Benkarim, Gemma Piella, Karim Lekadir, Nadine Hahner, Elisenda Eixarch, Miguel A González Ballester
Segmentation of brain structures during the pre-natal and early post-natal periods is the first step for subsequent analysis of brain development. Segmentation techniques can be roughly divided into two families. The first, which we denote as registration-based techniques, rely on initial estimates derived by registration to one (or several) templates. The second family, denoted as learning-based techniques, relate imaging (and spatial) features to their corresponding anatomical labels. Each approach has its own qualities and both are complementary to each other...
August 28, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30205334/computer-aided-classification-of-prostate-cancer-grade-groups-from-mri-images-using-texture-features-and-stacked-sparse-autoencoder
#4
Bejoy Abraham, Madhu S Nair
A novel method to determine the Grade Group (GG) in prostate cancer (PCa) using multi-parametric magnetic resonance imaging (mpMRI) biomarkers is investigated in this paper. In this method, high-level features are extracted from hand-crafted texture features using a deep network of stacked sparse autoencoders (SSAE) and classified them using a softmax classifier (SMC). Transaxial T2 Weighted (T2W), Apparent Diffusion Coefficient (ADC) and high B-Value Diffusion-Weighted (BVAL) images obtained from PROSTATEx-2 2017 challenge dataset are used in this technique...
August 25, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30172091/automatic-polyp-frame-screening-using-patch-based-combined-feature-and-dictionary-learning
#5
Younghak Shin, Ilangko Balasingham
Polyps in the colon can potentially become malignant cancer tissues where early detection and removal lead to high survival rate. Certain types of polyps can be difficult to detect even for highly trained physicians. Inspired by aforementioned problem our study aims to improve the human detection performance by developing an automatic polyp screening framework as a decision support tool. We use a small image patch based combined feature method. Features include shape and color information and are extracted using histogram of oriented gradient and hue histogram methods...
August 22, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30142578/cerebrovascular-segmentation-of-tof-mra-based-on-seed-point-detection-and-multiple-feature-fusion
#6
Ruoxiu Xiao, Hui Ding, Fangwen Zhai, Wenjing Zhou, Guangzhi Wang
The accurate extraction of cerebrovascular structures from time-of-flight (TOF) data is important for diagnosis of cerebrovascular diseases and planning and navigation of neurosurgery. In this study, we proposed a cerebrovascular segmentation method based on automatic seed point detection and vascular multiple-feature fusion. First, the brain mask in the T1-MR image is detected to enable the extraction of the TOF brain structure by simultaneously acquiring the TOF image and its corresponding T1-MRI. Second, local maximum points are detected on three maximum-intensity projections of TOF-MRA data and then be traced back in three-dimensional space to detect seed points for the initialization of vascular segmentation...
August 1, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30093171/3-d-neural-denoising-for-low-dose-coronary-ct-angiography-ccta
#7
Michael Green, Edith M Marom, Eli Konen, Nahum Kiryati, Arnaldo Mayer
CCTA has become an important tool for coronary arteries assessment in low and medium risk patients. However, it exposes the patient to significant radiation doses, resulting from high image quality requirements and acquisitions at multiple cardiac phases. For widespread use of CCTA for coronary assessment, significant reduction of radiation exposure with minimal image quality loss is still needed. A neural denoising scheme, relying on a fully convolutional neural network (FCNN) architecture, is developed and applied to noisy CCTA...
July 29, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30172090/intraoperative-margin-assessment-of-human-breast-tissue-in-optical-coherence-tomography-images-using-deep-neural-networks
#8
Amal Rannen Triki, Matthew B Blaschko, Yoon Mo Jung, Seungri Song, Hyun Ju Han, Seung Il Kim, Chulmin Joo
Assessing the surgical margin during breast lumpectomy operations can avoid the need for additional surgery. Optical coherence tomography (OCT) is an imaging technique that has been proven to be efficient for this purpose. However, to avoid overloading the surgeon during the operation, automatic cancer detection at the surface of the removed tissue is needed. This work explores automated margin assessment on a sample of patient data collected at the Pathology Department, Severance Hospital (Seoul, South Korea)...
July 6, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30170273/optimization-of-macaque-brain-dmri-connectome-by-neuron-tracing-and-myelin-stain-data
#9
Tuo Zhang, Jun Kong, Ke Jing, Hanbo Chen, Xi Jiang, Longchuan Li, Lei Guo, Jianfeng Lu, Xiaoping Hu, Tianming Liu
Accurate assessment of connectional anatomy of primate brains can be an important avenue to better understand the structural and functional organization of brains. To this end, numerous connectome projects have been initiated to create a comprehensive map of the connectional anatomy over a large spatial expanse. Tractography based on diffusion MRI (dMRI) data has been used as a tool by many connectome projects in that it is widely used to visualize axonal pathways and reveal microstructural features on living brains...
June 25, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30056291/an-effective-teeth-recognition-method-using-label-tree-with-cascade-network-structure
#10
Kailai Zhang, Ji Wu, Hu Chen, Peijun Lyu
In this article, we apply the deep learning technique to medical field for the teeth detection and classification of dental periapical radiographs, which is important for the medical curing and postmortem identification. We detect teeth in an input X-ray image and distinguish them from different position. An adult usually has 32 teeth, and some of them are similar while others have very different shape. So there are 32 teeth position for us to recognize, which is a challenging task. Convolutional neural network is a popular method to do multi-class detection and classification, but it needs a lot of training data to get a good result if used directly...
September 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/30056290/contrast-enhanced-transthoracic-echocardiography-applied-in-evaluation-of-pulmonary-right-to-left-shunt-a-preliminary-study
#11
Cheng Feng, Tingting Luo, Yongfang Luo, Ningbo Zhao, Kun Huang, Chang Xiao
OBJECTIVE: To investigate the detection rate of patent foramen ovale-right to left shunt (PFO-RLS) and/or pulmonary-right to left shunt (P-RLS) via contrast-enhanced transthoracic echocardiography (c-TTE) in healthy participants, patients suffering from cryptogenic stroke and migraine with aura. METHODS: Initially, 20 healthy volunteers, 21 cases with cryptogenic stroke, and 18 cases with migraine aura were randomly selected, and all of them received c-TTE and transesophageal echocardiography (TEE) examinations...
September 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29890404/automatic-histologically-closer-classification-of-skin-lesions
#12
Pedro Pedrosa Rebouças Filho, Solon Alves Peixoto, Raul Victor Medeiros da Nóbrega, D Jude Hemanth, Aldisio Gonçalves Medeiros, Arun Kumar Sangaiah, Victor Hugo C de Albuquerque
According to the American Cancer Society, melanoma is one of the most common types of cancer in the world. In 2017, approximately 87,110 new cases of skin cancer were diagnosed in the United States alone. A dermatoscope is a tool that captures lesion images with high resolution and is one of the main clinical tools to diagnose, evaluate and monitor this disease. This paper presents a new approach to classify melanoma automatically using structural co-occurrence matrix (SCM) of main frequencies extracted from dermoscopy images...
September 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29885566/combined-radiogrammetry-and-texture-analysis-for-early-diagnosis-of-osteoporosis-using-indian-and-swiss-data
#13
Anu Shaju Areeckal, Jagannath Kamath, Sophie Zawadynski, Michel Kocher, Sumam David S
Osteoporosis is a bone disorder characterized by bone loss and decreased bone strength. The most widely used technique for detection of osteoporosis is the measurement of bone mineral density (BMD) using dual energy X-ray absorptiometry (DXA). But DXA scans are expensive and not widely available in low-income economies. In this paper, we propose a low cost pre-screening tool for the detection of low bone mass, using cortical radiogrammetry of third metacarpal bone and trabecular texture analysis of distal radius from hand and wrist radiographs...
September 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29870822/fast-anatomy-segmentation-by-combining-coarse-scale-multi-atlas-label-fusion-with-fine-scale-corrective-learning
#14
Hongzhi Wang, Deepika Kakrania, Hui Tang, Prasanth Prasanna, Tanveer Syeda-Mahmood
Deformable registration based multi-atlas segmentation has been successfully applied in a broad range of anatomy segmentation applications. However, the excellent performance comes with a high computational burden due to the requirement for deformable image registration and voxel-wise label fusion. To address this problem, we investigate the role of corrective learning (Wang et al., 2011) in speeding up multi-atlas segmentation. We propose to combine multi-atlas segmentation with corrective learning in a multi-scale analysis fashion for faster speeds...
September 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29775951/retinal-blood-vessel-segmentation-using-fully-convolutional-network-with-transfer-learning
#15
Zhexin Jiang, Hao Zhang, Yi Wang, Seok-Bum Ko
Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging...
September 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29800886/cerebral-activation-effects-of-acupuncture-at-yanglinquan-gb34-point-acquired-using-resting-state-fmri
#16
Liansheng Liu, Shuqi Chen, Daohui Zeng, Hengguo Li, Changzheng Shi, Lihong Zhang
OBJECTIVE: To explore the central mechanism of acupuncture points for regional homogeneity(ReHo) of resting state in brain function after acupuncture at GB34. METHODS: Ten healthy volunteers were enrolled, which included 4 males and 6 females, aged 20-34 years old with median age of 23. The GE Signa HDxt 3.0 T magnetic resonance imaging were performed before (control group) and after acupuncture at GB34, and differences of different brain ReHo of 2 groups by statistical parametric mapping (SPM8) software and ReHo data processing methods were analyzed...
July 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29753964/a-web-based-system-for-neural-network-based-classification-in-temporomandibular-joint-osteoarthritis
#17
Priscille de Dumast, Clément Mirabel, Lucia Cevidanes, Antonio Ruellas, Marilia Yatabe, Marcos Ioshida, Nina Tubau Ribera, Loic Michoud, Liliane Gomes, Chao Huang, Hongtu Zhu, Luciana Muniz, Brandon Shoukri, Beatriz Paniagua, Martin Styner, Steve Pieper, Francois Budin, Jean-Baptiste Vimort, Laura Pascal, Juan Carlos Prieto
OBJECTIVE: The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). METHODS: This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans...
July 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29753963/application-of-semi-automated-ultrasonography-on-nutritional-support-for-severe-acute-pancreatitis
#18
Ying Li, Yu Ye, Mei Yang, Haiying Ruan, Yuan Yu
OBJECTIVE: To evaluate the application value of semi-automated ultrasound on the guidance of nasogastrojejunal tube replacement for patients with acute severe pancreatitis (ASP), as well as the value of the nutritional support for standardized treatment in clinical practice. METHODS: The retrospective research was performed in our hospital, and 34 patients suffering from ASP were enrolled into this study. All these identified participants ever received CT scans in order to make definitive diagnoses...
July 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29738914/g4dari-geant4-gate-based-monte-carlo-simulation-interface-for-dosimetry-calculation-in-radiotherapy
#19
Faiçal A A Slimani, Mahdjoub Hamdi, M'hamed Bentourkia
Monte Carlo (MC) simulation is widely recognized as an important technique to study the physics of particle interactions in nuclear medicine and radiation therapy. There are different codes dedicated to dosimetry applications and widely used today in research or in clinical application, such as MCNP, EGSnrc and Geant4. However, such codes made the physics easier but the programming remains a tedious task even for physicists familiar with computer programming. In this paper we report the development of a new interface GEANT4 Dose And Radiation Interactions (G4DARI) based on GEANT4 for absorbed dose calculation and for particle tracking in humans, small animals and complex phantoms...
July 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29702348/exploring-diagnosis-and-imaging-biomarkers-of-parkinson-s-disease-via-iterative-canonical-correlation-analysis-based-feature-selection
#20
Luyan Liu, Qian Wang, Ehsan Adeli, Lichi Zhang, Han Zhang, Dinggang Shen
Parkinson's disease (PD) is a neurodegenerative disorder that progressively hampers the brain functions and leads to various movement and non-motor symptoms. However, it is difficult to attain early-stage PD diagnosis based on the subjective judgment of physicians in clinical routines. Therefore, automatic and accurate diagnosis of PD is highly demanded, so that the corresponding treatment can be implemented more appropriately. In this paper, we focus on finding the most discriminative features from different brain regions in PD through T1-weighted MR images, which can help the subsequent PD diagnosis...
July 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
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