Zobrazeno 1 - 10
of 3 884
pro vyhledávání: '"vessel segmentation"'
Publikováno v:
Discover Applied Sciences, Vol 6, Iss 11, Pp 1-16 (2024)
Abstract Hypertension is a primary risk factor for the onset of cardiocerebrovascular diseases, leading to increased mortality. In the early stages of hypertension, changes in the diameter of the retinal arteries and veins are closely observed. There
Externí odkaz:
https://doaj.org/article/dc8ebb32cbe8407aa8211e4a3c861e12
Publikováno v:
Current Directions in Biomedical Engineering, Vol 10, Iss 1, Pp 29-32 (2024)
Liver vessel segmentation in computed tomography represents a highly challenging task due to the imbalanced distribution within the liver parenchyma, the small and branched vessels with decreased image contrast to surrounding tissue and in general, d
Externí odkaz:
https://doaj.org/article/1fcca075d7af47f4b9ee3b755d89466f
Autor:
Chenfangqian Xu, Xiaoxin Guo, Guangqi Yang, Yihao Cui, Longchen Su, Hongliang Dong, Xiaoying Hu, Songtian Che
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract To solve the issue of diagnosis accuracy of diabetic retinopathy (DR) and reduce the workload of ophthalmologists, in this paper we propose a prior-guided attention fusion Transformer for multi-lesion segmentation of DR. An attention fusion
Externí odkaz:
https://doaj.org/article/6ffa07b3ee654fa3a63f925b93cf42cb
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 213-224 (2024)
The intricate task of precisely segmenting retinal vessels from images, which is critical for diagnosing various eye diseases, presents significant challenges for models due to factors such as scale variation, complex anatomical patterns, low contras
Externí odkaz:
https://doaj.org/article/24ff6196ab994c96a17a781d636d7ab0
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract This study introduces a novel self-supervised learning method for single-frame subtraction and vessel segmentation in coronary angiography, addressing the scarcity of annotated medical samples in AI applications. We pretrain a U-Net model on
Externí odkaz:
https://doaj.org/article/d72f6a4d722c48e3b008b8c05e8415f5
Autor:
Mufassir Matloob Abbasi, Shahzaib Iqbal, Khursheed Aurangzeb, Musaed Alhussein, Tariq M. Khan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Blinding eye diseases are often related to changes in retinal structure, which can be detected by analysing retinal blood vessels in fundus images. However, existing techniques struggle to accurately segment these delicate vessels. Although
Externí odkaz:
https://doaj.org/article/69cf44581bf2450b85b6e3a74ef8e2f2
Autor:
Qingyou Liu, Fen Zhou, Jianxin Shen, Jianguo Xu, Cheng Wan, Xiangzhong Xu, Zhipeng Yan, Jin Yao
Publikováno v:
Frontiers in Cell and Developmental Biology, Vol 12 (2024)
BackgroundFundus vessel segmentation is vital for diagnosing ophthalmic diseases like central serous chorioretinopathy (CSC), diabetic retinopathy, and glaucoma. Accurate segmentation provides crucial vessel morphology details, aiding the early detec
Externí odkaz:
https://doaj.org/article/e96df749d6394642b0870814d793c9fb
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Background Segmenting liver vessels from contrast-enhanced computed tomography images is essential for diagnosing liver diseases, planning surgeries and delivering radiotherapy. Nevertheless, identifying vessels is a challenging task due to
Externí odkaz:
https://doaj.org/article/80137699d17d469e9f7077b84dcfa410
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-16 (2024)
Abstract Even though deep learning is fascinated in fields of coronary vessel segmentation in X-ray angiography and achieves prominent progresses, most of those models probably bring high false and missed detections due to indistinct contrast between
Externí odkaz:
https://doaj.org/article/99c8da19743b4c7da9f7f8ddbf487bf8
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