Renal ultrasound image segmentation method based on channel attention and GL-UNet11-Reference-Cited by-同舟云学术

Renal ultrasound image segmentation method based on channel attention and GL-UNet11

Published:2023-09 Issue:3 Volume:16 Page:100631
ISSN:1687-8507
Container-title:Journal of Radiation Research and Applied Sciences
language:en
Short-container-title:Journal of Radiation Research and Applied Sciences

Author:

Chen Shao-Hua,Wu Yan-Ling,Pan Can-Yu,Lian Luo-Yu,Su Qi-Chen

Publisher

Elsevier BV

Subject

General Medicine

Reference42 articles.

1. A deep convolutional encoder-decoder architecture for image segmentation;Badrinarayanan;IEEE Transactions on Pattern Analysis and Machine Intelligence,2017

2. The relationShip between uric acid, allopurinol, cardiovascular events, and kidney disease progression: A step forward;Bellomo;American Journal of Kidney Diseases the Official Journal of the National Kidney Foundation,2015

3. Sonographic renal parenchymal and pelvicaliceal areas;Cost;The Journal of Urology,1996

4. A calibration-based hybrid transfer learning framework for RUL prediction of rolling bearing across different machines;Deng;IEEE Transactions on Instrumentation and Measurement,2023

5. Non - parametric iterative model constraint graph min-segment for automatic kidney segmentation;Freiman;International Conference on Medical Image Computing and Computer-Assisted Intervention,2010

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1. Ultrasound Image Segmentation and its Evaluation using Various Encoder Architectures;2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS);2024-06-26

2. Advancements in Automatic Kidney Segmentation Using Deep Learning Frameworks and Volumetric Segmentation Techniques for CT Imaging: A Review;Archives of Computational Methods in Engineering;2024-02-19

3. Transformers and their application to medical image processing: A review;Journal of Radiation Research and Applied Sciences;2023-12