Weakly supervised segmentation of tumor lesions in PET-CT hybrid imaging-Reference-Cited by-同舟云学术

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Weakly supervised segmentation of tumor lesions in PET-CT hybrid imaging

Published:2021-10-13 Issue:05 Volume:8 Page:
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Früh Marcel¹,Fischer Marc²,Schilling Andreas³,Gatidis Sergios¹,Hepp Tobias¹

Affiliation:

1. University Hospital Tübingen, Department of Diagnostic and Interventional Radiology, Tübingen

2. University of Stuttgart, Institute of Signal Processing and System Theory, Stuttgart

3. University of Tübingen, Institute for Visual Computing, Department of Computer Science, Tübingen

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology, Nuclear Medicine and imaging

Cited by 6 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. Neural Network Classification Algorithm Based on Self-attention Mechanism and Ensemble Learning for MASLD Ultrasound Images;Ultrasound in Medicine & Biology;2024-09

2. Weakly supervised segmentation models as explainable radiological classifiers for lung tumour detection on CT images;Insights into Imaging;2023-11-19

3. Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population;PLOS ONE;2023-11-07

4. A Decision Support System for the Identification of Metastases of Metastatic Melanoma Using Whole-Body FDG PET/CT Images;IEEE Journal of Biomedical and Health Informatics;2023-03

5. Self-supervised learning for automated anatomical tracking in medical image data with minimal human labeling effort;Computer Methods and Programs in Biomedicine;2022-10

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