A Feature-Pooling and Signature-Pooling Method for Feature Selection for Quantitative Image Analysis: Application to a Radiomics Model for Survival in Glioma. - Zhenwei Shi; Chong Zhang; Inge Compter; Maikel Verduin; Ann Hoeben; Danielle Eekers; Andre Dekker; Leonard Wee (RNO-AI@MICCAI, 2019)

FAIR Quantitative Imaging in Oncology: how Semantic Web and Ontologies will support Reproducible Science. - Alberto Traverso; Zhenwei Shi; Leonard Wee; Andre Dekker (SWAT4HCLS, 2019)

Publishing Linked and FAIR-compliant Radiomics Data in Radiation Oncology via Ontologies and Semantic Web Techniques. - Alberto Traverso; Martin Vallières; Johan van Soest; Leonard Wee; Olivier Morin; Andre Dekker (SWAT4HCLS, 2019)

Auto Segmentation of Lung in Non-small Cell Lung Cancer Using Deep Convolution Neural Network. - Ravindra Patil; Leonard Wee; Andre Dekker (ICACDS, 2020)

Non-invasive prediction of lymph node risk in oral cavity cancer patients using a combination of supervised and unsupervised machine learning algorithms. - Alberto Traverso; Ali Hosni-Abdalaty; Mohammad Hasan; Tony Tadic; Tirth Patel; Meredith Giuliani; John Kim; Jolie Ringash; John Cho; Scott V. Bratman; Andrew Bayley; John Waldron; et al. (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics. - Siva Teja Kakileti; Himanshu J. Madhu; Geetha Manjunath; Leonard Wee; Andre Dekker; Sudhakar Sampangi (Artif. Intell. Medicine, 2020)

Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics. - Junhua Chen 002; Haiyan Zeng; Chong Zhang; Zhenwei Shi; Andre Dekker; Leonard Wee; Iñigo Bermejo (CoRR, 2021)

Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study. - Junhua Chen 002; Chong Zhang; Alberto Traverso; Ivan Zhovannik; Andre Dekker; Leonard Wee; Iñigo Bermejo (CoRR, 2021)

Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study. - Junhua Chen 002; Iñigo Bermejo; Andre Dekker; Leonard Wee (CoRR, 2021)

Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients. - Leanne L. G. C. Ackermans; Leroy Volmer; Leonard Wee; Ralph Brecheisen; Patricia Sánchez-González; Alexander P. Seiffert; Enrique J. Gómez; Andre Dekker; Jan A. Ten Bosch; Steven M. W. Olde Damink; Taco J. Blokhuis (Sensors, 2021)

Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark. - Parnian Afshar; Arash Mohammadi 001; Konstantinos N. Plataniotis; Keyvan Farahani; Justin S. Kirby; Anastasia Oikonomou; Amir Asif; Leonard Wee; Andre Dekker; Xin Wu; Mohammad Ariful Haque; Shahruk Hossain; et al. (CoRR, 2022)

Privacy-Preserving Dashboard for F.A.I.R Head and Neck Cancer data supporting multi-centered collaborations. - Varsha Gouthamchand; Ananya Choudhury; Frank Hoebers; Frederik Wesseling; Mattea Welch; Sejin Kim; Benjamin Haibe-Kains; Joanna Kazmierska; Andre Dekker; Johan van Soest; Leonard Wee (SWAT4HCLS, 2023)

Are all shortcuts in encoder-decoder networks beneficial for CT denoising? - Junhua Chen 002; Chong Zhang; Leonard Wee; Andre Dekker; Iñigo Bermejo (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2023)

Systematic review and meta-analysis of prediction models used in cervical cancer. - Ashish Kumar Jha 002; Sneha Mithun; Umeshkumar B. Sherkhane; Vinay Jaiswar; Biche Osong; Nilendu Purandare; Sadhana Kannan; Kumar Prabhash; Sudeep Gupta; Ben G. L. Vanneste; Venkatesh Rangarajan; Andre Dekker; et al. (Artif. Intell. Medicine, 2023)

Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma. - Sneha Mithun; Ashish Kumar Jha 002; Umeshkumar B. Sherkhane; Vinay Jaiswar; Nilendu Purandare; Andre Dekker; Sander Puts; Iñigo Bermejo; Venkatesh Rangarajan; Catharina M. L. Zegers; Leonard Wee (J. Digit. Imaging, 2023)

GAN-based one dimensional medical data augmentation. - Ye Zhang; Zhixiang Wang; Zhen Zhang 058; Junzhuo Liu 001; Ying Feng; Leonard Wee; Andre Dekker; Qiaosong Chen; Alberto Traverso (Soft Comput., 2023)

External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer. - Ashish Kumar Jha 002; Umeshkumar B. Sherkhane; Sneha Mithun; Vinay Jaiswar; Nilendu Purandare; Kumar Prabhash; Leonard Wee; Venkatesh Rangarajan; Andre Dekker (J. Digit. Imaging, 2023)

SwinHR: Hemodynamic-powered hierarchical vision transformer for breast tumor segmentation. - Zhihe Zhao; Siyao Du; Zeyan Xu; Zhi Yin; Xiaomei Huang; Xin Huang; Chinting Wong; Yanting Liang; Jing Shen; Jianlin Wu; Jinrong Qu; Lina Zhang; et al. (Comput. Biol. Medicine, 2024)

Data-efficient federated semi-supervised learning framework via pseudo supervision refinement strategy for lung tumor segmentation. - Weixing Li; Xipeng Pan; Zhen Zhang 058; Guangyao Wu; Guanchao Ye; Leonard Wee; Andre Dekker; Chu Han; Lei Shi; Zaiyi Liu; Zhenbing Liu; Zhenwei Shi (Biomed. Signal Process. Control., 2025)

Label-efficient transformer-based framework with self-supervised strategies for heterogeneous lung tumor segmentation. - Zhenbing Liu; Weixing Li; Yanfen Cui; Xin Chen 058; Xipeng Pan; Guanchao Ye; Guangyao Wu; Yongde Liao; Leroy Volmer; Leonard Wee; Andre Dekker; Chu Han; et al. (Expert Syst. Appl., 2025)