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Ambiguous Medical Image Segmentation Using Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2023 Collective insights from a group of experts have always proven to outperform an individual's best diagnostic for clinical tasks. For the task of medical image segmentation, existing research on AI-based alternatives focuses more on developing models that
Aimon Rahman +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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Neutrosophic DICOM Image Processing and its applications [PDF]
Neutrosophic Sets and Systems, 2023 Medical images are essential in contemporary medicine because they provide practicable entropy, which is used to diagnose medical conditions. It is useful to visualize abnormality in several parts of the body.
D. Nagarajan, S. Broumi
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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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Semi-supervised Medical Image Segmentation through Dual-task Consistency [PDF]
AAAI Conference on Artificial Intelligence, 2020 Deep learning-based semi-supervised learning (SSL) algorithms have led to promising results in medical images segmentation and can alleviate doctors' expensive annotations by leveraging unlabeled data.
Xiangde Luo +5 more
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Channel prior convolutional attention for medical image segmentation [PDF]
Comput. Biol. Medicine, 2023 Characteristics such as low contrast and significant organ shape variations are often exhibited in medical images. The improvement of segmentation performance in medical imaging is limited by the generally insufficient adaptive capabilities of existing ...
He-lu Huang +4 more
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Brain Image Segmentation Based on Fuzzy Clustering
Al-Mustansiriyah Journal of Science, 2018 The segmentation performance is topic to suitable initialization and best configuration of supervisory parameters. In medical image segmentation, the segmentation is very important when the diagnosing becomes very hard in medical images which are not ...
Mohammed Y. Kamil
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Frontiers in Public Health, 2022 To avoid the problems of relative overlap and low signal-to-noise ratio (SNR) of segmented three-dimensional (3D) multimodal medical images, which limit the effect of medical image diagnosis, a 3D multimodal medical image segmentation algorithm using ...
Weiwei Gao +3 more
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Semi-supervised Learning for Real-time Segmentation of Ultrasound Video Objects: A Review [PDF]
Advanced Ultrasound in Diagnosis and Therapy, 2023 Real-time intelligent segmentation of ultrasound video object is a demanding task in the field of medical image processing and serves as an essential and critical step in image-guided clinical procedures.
Jin Guo, MD, Zhaojun Li, PhD, Yanping Lin, PhD
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DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation [PDF]
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), 2020 Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the
Debesh Jha +4 more
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