Texture-Unet: A Texture-Aware Network for Bone Marrow Smear Whole-Slide Image Region of Interest Segmentation-Reference-Cited by-同舟云学术

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Texture-Unet: A Texture-Aware Network for Bone Marrow Smear Whole-Slide Image Region of Interest Segmentation

Published:2024-04-14 Issue: Volume: Page:2006-2010
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Chen Jian¹,Wu Xing¹,Wang Chengliang¹,Yang Zailin²,Wu XueLian²,Ran Longrong²,Liu Yao²

Affiliation:

1. Chongqing University,College of Computer Science,Chongqing,China,400000

2. Chongqing University Cancer Hospital,Department of Hematology-Oncology, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment,Chongqing,China,400000

Funder

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447261.pdf?arnumber=10447261

Reference18 articles.

1. Human-level recognition of blast cells in acute myeloid leukaemia with convolutional neural networks

2. Comparison of traditional image processing and deep learning approaches for classification of white blood cells in peripheral blood smear images

3. LeuFeatx: Deep learning–based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear

4. ICSH guidelines for the standardization of bone marrow specimens and reports

5. Automated bone marrow cytology using deep learning to generate a histogram of cell types

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