Results 31 to 40 of about 6,997,548 (275)
An improved U-shaped network for brain tumor segmentation
工程科学学报, 2023 Accurate segmentation of brain tumors from magnetic resonance images is the key to the clinical diagnosis and rational treatment of brain tumor diseases. Recently, convolutional neural networks have been widely used in biomedical image processing.
Jing-teng HUANG, Qiang LI, Xin GUAN
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Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition
CoRR, 2022 The Weather4Cast competition (hosted by NeurIPS 2022) required competitors to predict super-resolution rain movies in various regions of Europe when low-resolution satellite contexts covering wider regions are given. In this paper, we show that a general baseline 3D U-Net can be significantly improved with region-conditioned layers as well as ...
Taehyeon Kim 0001 +6 more
openaire +3 more sources
GAU U-Net for multiple sclerosis segmentation
Alexandria Engineering Journal, 2023 Multiple sclerosis is an auto immune disease which affects the brain and nervous system. A total of 2.8 million people are estimated to live with Multiple sclerosis worldwide (35.9 per 100,000 population).
Roba Gamal, Hoda Barka, Mayada Hadhoud
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Applied Sciences, 2023 Breast cancer ranks among the leading causes of death for women globally, making it imperative to swiftly and precisely detect the condition to ensure timely treatment and enhanced chances of recovery.
Saman Khalil +9 more
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Body Location Embedded 3D U-Net (BLE-U-Net) for Ovarian Cancer Ascites Segmentation on CT scans. [PDF]
Proc SPIE Int Soc Opt Eng, 2023 Ascites is often regarded as the hallmark of advanced ovarian cancer, which is the most lethal gynecologic malignancy. Ascites segmentation contributes to track the progress of ovarian cancer development by providing accurate ascites measurement, which can effectively guide subsequent treatment and potentially reduce the mortality.
Nag MK +6 more
europepmc +3 more sources
, 2021 Purpose: Automation of organ segmentation, via convolutional neural networks (CNNs), is key to facilitate the work of medical practitioners by ensuring that the adequate radiation dose is delivered to the target area while avoiding harmful exposure of ...
Macq, Benoît +7 more
core +1 more source
Direct quantification of epistemic and aleatoric uncertainty in 3D U-net segmentation. [PDF]
J Med Imaging (Bellingham), 2022 Purpose: To derive a multinomial probability function and quantitative measures of the data and epistemic uncertainty as direct output of a 3D U-Net segmentation network. Approach: A set of T1 brain MRI images were downloaded from the Connectome Project and segmented using FMRIB's FAST algorithm to be used as ground truth. A 3D U-Net neural network was
Jones CK, Wang G, Yedavalli V, Sair H.
europepmc +3 more sources
Segmentation result for each label in 2D and 3D U-Net according to the secondary labelling effect.
, 2022 Segmentation result for each label in 2D and 3D U-Net according to the secondary labelling effect.
Eui-sup Lee (13933194) +6 more
core +1 more source
PLoS ONE, 2023 IntroductionRotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnostic modality for RCT, but the interpretation of the results is tedious and has some reliability issues. In
Su Hyun Lee +6 more
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A Multi Brain Tumor Region Segmentation Model Based on 3D U-Net
Applied Sciences, 2023 Accurate segmentation of different brain tumor regions from MR images is of great significance in the diagnosis and treatment of brain tumors. In this paper, an enhanced 3D U-Net model was proposed to address the shortcomings of 2D U-Net in the ...
Zhenwei Li, Xiaoqin Wu, Xiaoli Yang
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