A Semi-supervised method for tumor segmentation in mammogram images-Reference-Cited by-同舟云学术

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A Semi-supervised method for tumor segmentation in mammogram images

Published:2020 Issue:1 Volume:10 Page:12
ISSN:2228-7477
Container-title:Journal of Medical Signals & Sensors
language:en
Short-container-title:J Med Signals Sens

Author:

Abdoos Monireh,Azary Hanie

Publisher

Medknow

Subject

Health Informatics,Radiology Nuclear Medicine and imaging,Biomedical Engineering,Radiological and Ultrasound Technology,Computer Science (miscellaneous)

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Effectiveness of Semi-Supervised Learning Techniques in Identifying Calcifications in X-ray Mammography and the Impact of Different Classification Probabilities;Applied Sciences;2024-07-09

2. ME-CCNN: Multi-encoded images and a cascade convolutional neural network for breast tumor segmentation and recognition;Artificial Intelligence Review;2023-02-18

3. A Review of the Role of Ultrasound Radiomics and Its Application and Limitations in the Investigation of Thyroid Disease;Medical Science Monitor;2022-09-23

4. Semi-supervised learning in cancer diagnostics;Frontiers in Oncology;2022-07-14

5. MRFE-CNN: multi-route feature extraction model for breast tumor segmentation in Mammograms using a convolutional neural network;Annals of Operations Research;2022-05-26

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