Tumor-aware augmentation with task-guided attention analysis improves rectal cancer segmentation from magnetic resonance images
Authors:
- Aneesh RangnekarARAneesh Rangnekar
- Joao MirandaJMJoao Miranda
- Natally HorvatNHNatally Horvat
- Stephanie ChahwanSCStephanie Chahwan
- Samir AlrayessSASamir Alrayess
- Aditya ApteAAAditya Apte
- Aditi IyerAIAditi Iyer
- Eve LoCastroELEve LoCastro
- Revathi RavellaRRRevathi Ravella
- Marc J. GollubMGMarc J. Gollub
- Iva PetkovskaIPIva Petkovska
- Jesse Joshua SmithJSJesse Joshua Smith
- 21 August 2026
- journal article
- Published by Elsevier in Biomedical Signal Processing and Control
- Vol. 128
Abstract
No abstract availableAll Related Versions
Funding Information
- Simons Foundation
- Breast Cancer Research Foundation (MATH-23-001)
This publication has 26 references indexed in Scilit:
- Leading Cancer Deaths in People Younger Than 50 YearsJAMA, 2026
- Reliability of rectal MRI radiomic features: Comparing rectal MRI radiomic features across reader expertise levels, image segmentation technique, and timing of rectal MRI in patients with locally advanced rectal cancerEuropean Journal of Radiology, 2025
- Self‐supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differencesMedical Physics, 2024
- TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformersMedical Image Analysis, 2024
- Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learningEuropean Radiology, 2023
- MRI-based radiomic score increased mrTRG accuracy in predicting rectal cancer response to neoadjuvant therapyAbdominal Radiology, 2023
- Clinical utility of radiomics at baseline rectal MRI to predict complete response of rectal cancer after chemoradiation therapyAbdominal Radiology, 2020
- Reliability of tumor segmentation in glioblastoma: Impact on the robustness of MRI‐radiomic featuresMedical Physics, 2019
- Magnetic resonance imaging for clinical management of rectal cancer: Updated recommendations from the 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) consensus meetingEuropean Radiology, 2017
- The accuracy of Multi-detector row CT for the assessment of tumor invasion of the mesorectal fascia in primary rectal cancerAbdominal Radiology, 2008