Results 11 to 20 of about 17,459,905 (291)
Loss Odyssey in Medical Image Segmentation
Medical Image Analysis, 2021 New segmentation results (based on nnUNetV2) of different loss functions in "Loss Odyssey in Medical Image Segmentation"
Jun Ma
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Segment anything in medical images
Nature CommunicationsMedical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability
Jun Ma +5 more
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Medical imaging analysis with artificial neural networks [PDF]
, 2010 Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection ...
Jiang, J., Ren, Jinchang, Trundle, P.
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The semiotics of medical image Segmentation [PDF]
Medical Image Analysis, 2018 As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive ...
John S. H. Baxter +3 more
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Automatic texture segmentation for content-based image retrieval application [PDF]
, 2006 In this article, a brief review on texture segmentation is presented, before a novel automatic texture segmentation algorithm is developed. The algorithm is based on a modified discrete wavelet frames and the mean shift algorithm.
Fauzi, M.F.A. +3 more
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Active contours based on weighted gradient vector flow and balloon forces for medical image segmentation [PDF]
, 2014 Active contours, or snakes, have been widely used for image segmentation purposes. However, high noise sensitivity and poor performance over weak edges are the most acute issues that hinder the segmentation accuracy of these curves, particularly in ...
Victor Sanchez +5 more
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3D medical volume segmentation using hybrid multiresolution statistical approaches [PDF]
, 2010 This article is available through the Brunel Open Access Publishing Fund. Copyright © 2010 S AlZu’bi and A Amira.3D volume segmentation is the process of partitioning voxels into 3D regions (subvolumes) that represent meaningful physical entities which ...
Alzubi, S +3 more
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Fully Convolutional Network for the Semantic Segmentation of Medical Images: A Survey
Diagnostics, 2022 There have been major developments in deep learning in computer vision since the 2010s. Deep learning has contributed to a wealth of data in medical image processing, and semantic segmentation is a salient technique in this field.
Sheng-Yao Huang +3 more
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Review of U-Net-Based Convolutional Neural Networks for Breast Medical Image Segmentation [PDF]
Jisuanji kexue yu tansuoU-Net and its variants have showcased exceptional performance in the domain of breast medical image segmentation. By employing a fully convolutional network (FCN) structure for semantic segmentation, the symmetrical structure of U-Net offers remarkable ...
PU Qiumei, YIN Shuai, LI Zhengmao, ZHAO Lina
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Digital Medical Image Segmentation Using Fuzzy C-Means Clustering
UHD Journal of Science and Technology, 2020 In the modern globe, digital medical image processing is a major branch to study in the fields of medical and information technology. Every medical field relies on digital medical imaging in diagnosis for most of their cases.
Bakhtyar Ahmed Mohammed +1 more
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