An Efficient Rapid Region Growing Algorithm for Medical Image Segmentation [PDF]
, 2023 Medical imaging is an important diagnostic tool, so that medical personnel can more easily understand the patient's condition. Therefore, this study will combine medical knowledge and computer science to detect and capture the various features.
Chen*, Chii-Jen
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A medical image segmentation method based on multi-dimensional statistical features
Frontiers in Neuroscience, 2022 Medical image segmentation has important auxiliary significance for clinical diagnosis and treatment. Most of existing medical image segmentation solutions adopt convolutional neural networks (CNNs).
Yang Xu +9 more
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Transforming the Interactive Segmentation for Medical Imaging
, 2022 Accepted to MICCAI ...
Wentao Liu +4 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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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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Efficient Subclass Segmentation in Medical Images
, 2023 As research interests in medical image analysis become increasingly fine-grained, the cost for extensive annotation also rises. One feasible way to reduce the cost is to annotate with coarse-grained superclass labels while using limited fine-grained annotations as a complement.
Linrui Dai +2 more
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Object segmentation by fitting statistical shape models : a Kernel-based approach with application to wisdom tooth segmentation from CBCT images [PDF]
, 2014 Image segmentation is an important and challenging task in medical image analysis. Especially from low-quality images, segmentation algorithms have to cope with misleading background clutter, insufficient object boundaries and noise in the image ...
Jud, Christoph
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Interaction in the segmentation of medical images: A survey
Medical Image Analysis, 2001 Segmentation of the object of interest is a difficult step in the analysis of digital images. Fully automatic methods sometimes fail, producing incorrect results and requiring the intervention of a human operator. This is often true in medical applications, where image segmentation is particularly difficult due to restrictions imposed by image ...
Olabarriaga, S.D., Smeulders, A.W.M.
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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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