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Medical Physics|June 6, 2017
A random walk-based segmentation framework for 3D ultrasound images of the prostateLing Ma, Rongrong Guo, Zhiqiang Tian, et al.
Proceedings of Spie--The International Society for Optical Engineering|January 2, 2026
A spatial-spectral vision transformer model for head and neck cancer detection with hyperspectral, RGB, and synthesized RGB histologic imagesHemanth Pasupuleti, Ling Ma, Xiaohu Guo, et al.
Proceedings of Spie--The International Society for Optical Engineering|February 16, 2023
Unsupervised Super Resolution Network for Hyperspectral Histologic ImagingLing Ma, Armand Rathgeb, Minh Tran, et al.
Proceedings of Spie--The International Society for Optical Engineering|March 19, 2024
Extended Depth of Field Imaging for Mosaic Hyperspectral ImagesArmand Rathgeb, Ling Ma, Minh Tran, et al.
Journal of Biomedical Optics|March 23, 2026
Medical hyperspectral imaging: an updated review of technology advancements and biomedical applicationsMinh H Tran, Ling Ma, Mandy Yuan, et al.
Journal of Medical Imaging (Bellingham, Wash.)|June 19, 2026
High-speed optical tracking and augmented reality platform for image-guided interventionsNati Nawawithan, James Yu, Kelden Pruitt, et al.
Proceedings of Spie--The International Society for Optical Engineering|October 22, 2025
Novel view synthesis using neural radiance fields for laparoscopic surgery navigationNati Nawawithan, James Yu, Kelden Pruitt, et al.
Proceedings of Spie--The International Society for Optical Engineering|June 25, 2020
Development of a new polarized hyperspectral imaging microscopeXiming Zhou, Ling Ma, Martin Halicek, et al.
Journal of Biomedical Optics|May 24, 2022
Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging (Errata)Ling Ma, Armand Rathgeb, Hasan Mubarak, et al.
Proceedings of Spie--The International Society for Optical Engineering|June 2, 2020
Hyperspectral Microscopic Imaging for Automatic Detection of Head and Neck Squamous Cell Carcinoma Using Histologic Image and Machine LearningLing Ma, Martin Halicek, Ximing Zhou, et al.
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