Preprocessing Techniques for Rectal Cancer Diagnosis using MR Images-Reference-Cited by-同舟云学术

Preprocessing Techniques for Rectal Cancer Diagnosis using MR Images

Published:2024-02 Issue: Volume:14 Page:185-191
ISSN:
Container-title:Proceedings of the 2024 13th International Conference on Software and Computer Applications
language:
Short-container-title:

Author:

D'Almeida Sonal Patreena¹^ORCID,Kamath Surekha¹^ORCID,K V Rajagopal²^ORCID,K.N Manjunath³^ORCID

Affiliation:

1. Department of Instrumentation and Control Engineering , Manipal Institute of Technology Manipal, Manipal Academy of Higher Education, India

2. Department of Radiodiagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education, India

3. Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education,, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3651781.3651809

Reference18 articles.

1. Automatic Prediction of T2/T3 Staging of Rectal Cancer Based on Radiomics and Machine Learning

2. Deep-learning-based 3D super-resolution MRI radiomics model: superior predictive performance in preoperative T-staging of rectal cancer

3. Doenja Lambregts Rhiannon van Loenhout Frank Zijta Max Lahaye Regina Beets-Tan and Robin Smithuis “Rectal Cancer MR staging 3.0 ” Radiology Departement of the Netherlands Cancer Institute in Amsterdam the Medical Centre Haaglanden in the Hague and the Alrijne Hospital in Leiderdorp the Netherlands.

4. Z. Sang, C. Li, Y. Xu, Y. Wang, H. Zheng, and Y. Guo, “FCTformer: Fusing convolutional operations and Transformer for 3D Rectal Tumor Segmentation in MR images,” IEEE Access, 2024.

5. RTAU-Net: A novel 3D rectal tumor segmentation model based on dual path fusion and attentional guidance