Monika Grewal

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 15

Top Topics

Cervical Cancer

Top Venues

Medical Imaging: Image Processing

Publications

Monika Grewal, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten
Multi-Objective Learning for Deformable Image Registration. CoRR (2024)
Monika Grewal, Dustin van Weersel, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten
Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. CoRR (2023)
Monika Grewal, Dustin van Weersel, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten
Learning Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. MIDL (2023)
Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers, Tanja Alderliesten, Peter A. N. Bosman
Multi-objective Learning Using HV Maximization. EMO (2023)
Martijn M. A. Bosma, Arkadiy Dushatskiy, Monika Grewal, Tanja Alderliesten, Peter A. N. Bosman
Mixed-block neural architecture search for medical image segmentation. Medical Imaging: Image Processing (2022)
Martijn M. A. Bosma, Arkadiy Dushatskiy, Monika Grewal, Tanja Alderliesten, Peter A. N. Bosman
Mixed-Block Neural Architecture Search for Medical Image Segmentation. CoRR (2022)
Monika Grewal, Jan Wiersma, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten
Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration. CoRR (2021)
Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers, Tanja Alderliesten, Peter A. N. Bosman
Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization. CoRR (2021)
Monika Grewal, Timo M. Deist, Jan Wiersma, Peter A. N. Bosman, Tanja Alderliesten
An end-to-end deep learning approach for landmark detection and matching in medical images. Medical Imaging: Image Processing (2020)
Monika Grewal, Timo M. Deist, Jan Wiersma, Peter A. N. Bosman, Tanja Alderliesten
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images. CoRR (2020)
Pulkit Kumar, Monika Grewal, Muktabh Mayank Srivastava
Boosted Cascaded Convnets for Multilabel Classification of Thoracic Diseases in Chest Radiographs. ICIAR (2018)
Monika Grewal, Muktabh Mayank Srivastava, Pulkit Kumar, Srikrishna Varadarajan
RADnet: Radiologist level accuracy using deep learning for hemorrhage detection in CT scans. ISBI (2018)
Srikrishna Varadarajan, Muktabh Mayank Srivastava, Monika Grewal, Pulkit Kumar
Anatomical labeling of brain CT scan anomalies using multi-context nearest neighbor relation networks. CoRR (2017)
Monika Grewal, Muktabh Mayank Srivastava, Pulkit Kumar, Srikrishna Varadarajan
RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans. CoRR (2017)
Pulkit Kumar, Monika Grewal, Muktabh Mayank Srivastava
Boosted Cascaded Convnets for Multilabel Classification of Thoracic Diseases in Chest Radiographs. CoRR (2017)