Automatic 3D CT liver segmentation based on fast global minimization of probabilistic active contour.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16116
Abstract: PURPOSE Automatic liver segmentation from computed tomography (CT) images is an essential preprocessing step for computer-aided diagnosis of liver diseases. However, due to the large differences in liver shapes, low-contrast to adjacent tissues, and existence… read more here.
Keywords: liver; automatic liver; liver segmentation; segmentation ... See more keywords
Liver segmentation in MRI images based on whale optimization algorithm
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-4638-5
Abstract: This paper proposes an approach for liver segmentation in MRI images based on Whale optimization algorithm (WOA). It is used to extract the different clusters in the abdominal image to support the segmentation process. A… read more here.
Keywords: mri images; segmentation mri; image; liver segmentation ... See more keywords
Incorporating prior shape knowledge via data-driven loss model to improve 3D liver segmentation in deep CNNs
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-019-02085-y
Abstract: Purpose Convolutional neural networks (CNNs) have obtained enormous success in liver segmentation. However, there are several challenges, including low-contrast images, and large variations in the shape, and appearance of the liver. Incorporating prior knowledge in… read more here.
Keywords: liver segmentation; knowledge; segmentation; model ... See more keywords
A variational approach to liver segmentation using statistics from multiple sources.
Sign Up to like & getrecommendations! Published in 2018 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/aaa360
Abstract: Medical image segmentation plays an important role in digital medical research, and therapy planning and delivery. However, the presence of noise and low contrast renders automatic liver segmentation an extremely challenging task. In this study,… read more here.
Keywords: see text; formula see; segmentation; liver segmentation ... See more keywords
Deep Belief Network Modeling for Automatic Liver Segmentation
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DOI: 10.1109/access.2019.2896961
Abstract: The liver segmentation in CT scan images is a significant step toward the development of a quantitative biomarker for computer-aided diagnosis. In this paper, we propose an automatic feature learning algorithm based on the deep… read more here.
Keywords: liver; belief network; liver segmentation; deep belief ... See more keywords
An Improved Confidence Connected Liver Segmentation Method Based on Three Views of CT Images
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2914856
Abstract: To enhance the accuracy of liver segmentation, we present an improved confidence connected liver segmentation method, which combines the liver segmentation results obtained from three views is proposed. First, to reduce noise, an improved curvature… read more here.
Keywords: liver segmentation; method; confidence connected; three views ... See more keywords
Multi-Stage Liver Segmentation in CT Scans Using Gaussian Pseudo Variance Level Set
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DOI: 10.1109/access.2021.3097387
Abstract: No single technology can be rich enough to segment accurately due to the challenges of liver segmentation, which include low contrast with neighboring organs and the presence of pathology as well as highly varied shapes… read more here.
Keywords: variance level; pseudo variance; liver segmentation; multi stage ... See more keywords
Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/2665283
Abstract: Segmentation of a liver in computed tomography (CT) images is an important step toward quantitative biomarkers for a computer-aided decision support system and precise medical diagnosis. To overcome the difficulties that come across the liver… read more here.
Keywords: liver; computed tomography; liver segmentation; segmentation ... See more keywords
A Lightweight Convolutional Neural Network Model for Liver Segmentation in Medical Diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/7954333
Abstract: Liver segmentation and recognition from computed tomography (CT) images is a warm topic in image processing which is helpful for doctors and practitioners. Currently, many deep learning methods are used for liver segmentation that takes… read more here.
Keywords: network; liver; convolutional neural; liver segmentation ... See more keywords