2 citations · 5 across the 3 of their papers we have counts for
3 papers
eess.IV2024★ 2 cited
Deep Learning-Based Correction and Unmixing of Hyperspectral Images for Brain Tumor Surgery
David Black, Jaidev Gill, Andrew Xie +4
Hyperspectral Imaging (HSI) for fluorescence-guided brain tumor resection enables visualization of differences between tissues that are not distinguishable to humans. This augmenta…
eess.IV2024★ 1 cited
A Spectral Library and Method for Sparse Unmixing of Hyperspectral Images in Fluorescence Guided Resection of Brain Tumors
David Black, Benoit Liquet, Sadahiro Kaneko +3
Through spectral unmixing, hyperspectral imaging (HSI) in fluorescence-guided brain tumor surgery has enabled detection and classification of tumor regions invisible to the human e…
q-bio.TO2023★ 2 cited
Towards Machine Learning-based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection
David Black, Declan Byrne, Anna Walke +6
Complete resection of malignant gliomas is hampered by the difficulty in distinguishing tumor cells at the infiltration zone. Fluorescence guidance with 5-ALA assists in reaching t…