Caln: Channel Attention LSTM Network for Pituitary Segmentation in Dynamic Contrast-Enhanced MRI-Reference-Cited by-同舟云学术

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Caln: Channel Attention LSTM Network for Pituitary Segmentation in Dynamic Contrast-Enhanced MRI

Published:2024-05-27 Issue: Volume:28 Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Liu Jingyi¹,Sun Zhaoze¹,Guo Qing¹,Liu Bing²,Fu Tianyu³,Ma Guolin²,Song Hong¹,Yang Jian⁴

Affiliation:

1. Beijing Institute of Technology,School of Computer Science and Technology,Beijing,China

2. China-Japan Friendship Hospital,Department of Radiology,Beijing,China

3. Beijing Institute of Technology,School of Medical Engineering,Beijing,China

4. Beijing Institute of Technology,School of Optics and Photonics,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635573.pdf?arnumber=10635573

Reference20 articles.

1. Estimating volumes of the pituitary gland from T1-weighted magnetic-resonance images: Effects of age, puberty, testosterone, and estradiol

2. Accuracy and reproducibility of a novel semi-automatic segmentation technique for MR volumetry of the pituitary gland

3. U-Net: Convolutional Networks for Biomedical Image Segmentation

4. Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images

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