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Leonard Wee
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2020 – today
- 2024
- [j8]Zhihe Zhao, Siyao Du, Zeyan Xu, Zhi Yin, Xiaomei Huang, Xin Huang, Chinting Wong, Yanting Liang, Jing Shen, Jianlin Wu, Jinrong Qu, Lina Zhang, Yanfen Cui, Ying Wang, Leonard Wee
, Andre Dekker
SwinHR: Hemodynamic-powered hierarchical vision transformer for breast tumor segmentation. Comput. Biol. Medicine 169: 107939 (2024) - 2023
- [j7]Ashish Kumar Jha
Systematic review and meta-analysis of prediction models used in cervical cancer. Artif. Intell. Medicine 139: 102549 (2023) - [j6]Junhua Chen
Are all shortcuts in encoder-decoder networks beneficial for CT denoising? Comput. methods Biomech. Biomed. Eng. Imaging Vis. 11(1): 59-66 (2023) - [j5]Sneha Mithun
Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma. J. Digit. Imaging 36(3): 812-826 (2023) - [j4]Ashish Kumar Jha
External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer. J. Digit. Imaging 36(6): 2519-2531 (2023) - [j3]Ye Zhang, Zhixiang Wang, Zhen Zhang, Junzhuo Liu
GAN-based one dimensional medical data augmentation. Soft Comput. 27(15): 10481-10491 (2023) - [c6]Varsha Gouthamchand, Ananya Choudhury, Frank Hoebers, Frederik Wesseling, Mattea Welch, Sejin Kim, Benjamin Haibe-Kains, Joanna Kazmierska, Andre Dekker, Johan van Soest, Leonard Wee:
Privacy-Preserving Dashboard for F.A.I.R Head and Neck Cancer data supporting multi-centered collaborations. SWAT4HCLS 2023: 11-21 - 2022
- [i4]Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis, Keyvan Farahani, Justin S. Kirby, Anastasia Oikonomou, Amir Asif, Leonard Wee, Andre Dekker, Xin Wu, Mohammad Ariful Haque, Shahruk Hossain, Md. Kamrul Hasan, Uday Kamal, Winston H. Hsu, Jhih-Yuan Lin, M. Sohel Rahman, Nabil Ibtehaz, Sh. M. Amir Foisol, Kin-Man Lam, Zhong Guang, Runze Zhang, Sumohana S. Channappayya, Shashank Gupta, Chander Dev:
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark. CoRR abs/2201.00458 (2022) - 2021
- [j2]Leanne L. G. C. Ackermans, Leroy Volmer, Leonard Wee
Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients. Sensors 21(6): 2083 (2021) - [i3]Junhua Chen
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics. CoRR abs/2104.14655 (2021) - [i2]Junhua Chen, Chong Zhang, Alberto Traverso, Ivan Zhovannik, Andre Dekker, Leonard Wee, Iñigo Bermejo:
Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study. CoRR abs/2104.15050 (2021) - [i1]Junhua Chen, Iñigo Bermejo, Andre Dekker, Leonard Wee:
Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study. CoRR abs/2109.02252 (2021) - 2020
- [j1]Siva Teja Kakileti, Himanshu J. Madhu, Geetha Manjunath, Leonard Wee, Andre Dekker, Sudhakar Sampangi:
Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics. Artif. Intell. Medicine 105: 101854 (2020) - [c5]Ravindra Patil, Leonard Wee, Andre Dekker:
Auto Segmentation of Lung in Non-small Cell Lung Cancer Using Deep Convolution Neural Network. ICACDS 2020: 340-351 - [c4]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, Brian O'Sullivan, Jonathan C. Irish, Douglas Chepeha, John De Almeida, David Goldstein, David A. Jaffray, Leonard Wee, Andre Dekker, Andrew Hope:
Non-invasive prediction of lymph node risk in oral cavity cancer patients using a combination of supervised and unsupervised machine learning algorithms. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 113172C
2010 – 2019
- 2019
- [c3]Zhenwei Shi
A Feature-Pooling and Signature-Pooling Method for Feature Selection for Quantitative Image Analysis: Application to a Radiomics Model for Survival in Glioma. RNO-AI@MICCAI 2019: 70-80 - [c2]Alberto Traverso, Zhenwei Shi, Leonard Wee, Andre Dekker:
FAIR Quantitative Imaging in Oncology: how Semantic Web and Ontologies will support Reproducible Science. SWAT4HCLS 2019: 122-126 - [c1]Alberto Traverso, Martin Vallières, Johan van Soest, Leonard Wee, Olivier Morin, Andre Dekker:
Publishing Linked and FAIR-compliant Radiomics Data in Radiation Oncology via Ontologies and Semantic Web Techniques. SWAT4HCLS 2019: 143-144
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last updated on 2024-11-28 21:25 CET by the dblp team
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