Branding/Logomark minus Citation Combined Shape Icon/Bookmark-empty Icon/Copy Icon/Collection Icon/Close Copy 7 no author result Created with Sketch. Icon/Back Created with Sketch. Match!
IEEE Transactions on Medical Imaging
Papers 4975
1 page of 498 pages (4,975 results)
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Hrvoje Bogunovic14
Estimated H-index: 14
(Medical University of Vienna),
Freerk Venhuizen4
Estimated H-index: 4
(Radboud University Nijmegen)
+ 29 AuthorsCarlos Ciller4
Estimated H-index: 4
Retinal swelling due to the accumulation of fluid is associated with the most vision-threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of care in assessing the presence and quantity of retinal fluid and image-guided treatment management. Deep learning methods have made their impact across medical imaging and many retinal OCT analysis methods have been proposed. But it is currently not clear how successful they are in interpreting retinal fluid on OCT, which...
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Huangjing Lin3
Estimated H-index: 3
(CUHK: The Chinese University of Hong Kong),
Hao Chen21
Estimated H-index: 21
+ 3 AuthorsPheng-Ann Heng46
Estimated H-index: 46
(CUHK: The Chinese University of Hong Kong)
Lymph node metastasis is one of the most important indicators in breast cancer diagnosis, that is traditionally observed under the microscope by pathologists. In recent years, with the dramatic advance of high-throughput scanning and deep learning technology, automatic analysis of histology from whole- slide images has received a wealth of interest in the field of medical image computing, which aims to alleviate pathologists’ workload and simultaneously reduce misdiagnosis rate. However, automat...
Published on Jan 1, 2018in IEEE Transactions on Medical Imaging 7.82
Fatemeh Taheri Dezaki1
Estimated H-index: 1
(UBC: University of British Columbia),
Zhibin Liao (UBC: University of British Columbia)+ 8 AuthorsPurang Abolmaesumi28
Estimated H-index: 28
(UBC: University of British Columbia)
Accurate detection of end-systolic (ES) and enddiastolic (ED) frames in an echocardiographic cine series can be a difficult but necessary pre-processing step for the development of automatic systems to measure cardiac parameters. The detection task is challenging due to variations in cardiac anatomy and heart rate often associated with pathological conditions. We formulate this problem as a regression problem, and propose several deep learning-based architectures that minimize a novel global ext...
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Jun Zhang6
Estimated H-index: 6
(Ha Tai: Xiamen University),
Jian Wu (Ha Tai: Xiamen University)+ 4 AuthorsZhong Chen18
Estimated H-index: 18
(Ha Tai: Xiamen University)
Quantitative magnetic resonance imaging (MRI) is of great value to both clinical diagnosis and scientific research. However, most MRI experiments remain qualitative, especially dynamic MRI, because repeated sampling with variable weighting parameter makes quantitative imaging time consuming and sensitive to motion artifacts. A single-shot quantitative T2 mapping method based on multiple overlapping-echo acquisition (dubbed MOLED-4) was proposed to obtain reliable T2 mapping in milliseconds. Diff...
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Leyuan Fang19
Estimated H-index: 19
(Hunan University),
Chong Wang1
Estimated H-index: 1
(Hunan University)
+ 3 AuthorsZhimin Liu (Hunan University)
Automatic and accurate classification of retinal optical coherence tomography (OCT) images is essential to assist ophthalmologist in the diagnosis and grading of macular diseases. Clinically, ophthalmologists usually diagnose macular diseases according to the structures of macular lesions, whose morphologies, size, and numbers are important criteria. In this paper, we propose a novel lesion-aware convolutional neural network (LACNN) method for retinal OCT image classification, in which retinal l...
Published on Jan 1, 2018in IEEE Transactions on Medical Imaging 7.82
Jaya Prakash7
Estimated H-index: 7
(IISc: Indian Institute of Science),
Dween Sanny1
Estimated H-index: 1
(IISc: Indian Institute of Science)
+ 2 AuthorsPhaneendra K. Yalavarthy14
Estimated H-index: 14
(IISc: Indian Institute of Science)
Photoacoustic tomography involves reconstructing the initial pressure rise distribution from the measured acoustic boundary data. The recovery of the initial pressure rise distribution tends to be an ill-posed problem in presence of noise and when limited independent data is available, necessitating regularization. The standard regularization schemes include, Tikhonov, l1-norm, and total-variation. These regularization schemes weigh the singular values equally irrespective of the noise level pre...
Published in IEEE Transactions on Medical Imaging 7.82
Yunze Man1
Estimated H-index: 1
Yangsibo Huang1
Estimated H-index: 1
+ -3 AuthorsFei Wu1
Estimated H-index: 1
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Haotian Xu2
Estimated H-index: 2
(WSU: Wayne State University),
Ming Dong24
Estimated H-index: 24
(WSU: Wayne State University)
+ 3 AuthorsJeong Won Jeong15
Estimated H-index: 15
(WSU: Wayne State University)
Convolutional neural networks (CNNs) have recently been used in biomedical imaging applications with great success. In this paper, we investigated the classi?cation performance of CNN models on diffusion weighted imaging (DWI) streamlines de?ned by functional MRI (fMRI) and electrical stimulation mapping (ESM). To learn a set of discriminative and interpretable features from the extremely unbalanced dataset, we evaluated different CNN architectures with multiple loss functions (e.g., focal loss ...
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
T. Speidel (University of Ulm), P. Metze , Volker Rasche27
Estimated H-index: 27
(University of Ulm)
The overall duration of acquiring a Nyquist sampled 3D dataset can be significantly shortened by enhancing the efficiency of k-space sampling. This can be achieved by increasing the coverage of k-space for every trajectory interleave. Further acceleration is possible by making use of advantageous undersampling properties. In this work, a versatile 3D centre-out k-space trajectory, based on Jacobian elliptic functions (Seiffert’s spiral) is presented. The trajectory leads to a lowdiscrepancy cove...
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Jana Lipková4
Estimated H-index: 4
(TUM: Technische Universität München),
Panagiotis Angelikopoulos (D. E. Shaw Research)+ 11 AuthorsPanagiotis Hadjidoukas1
Estimated H-index: 1
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate surrounding normal brain tissue beyond the lesion outlines visible in the current medical scans. These infiltrative cells are treated mainly by radiotherapy. Existing radiotherapy plans for brain tumors derive from population studies and scarcely account for patient-specific conditions. Here we provide a Bayesian machine learning framework for the rational design of improved, personalized radiotherapy plans using mathematical ...