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Guolan Lu

Researcher at Stanford University

Publications -  53
Citations -  3413

Guolan Lu is an academic researcher from Stanford University. The author has contributed to research in topics: Hyperspectral imaging & Cancer. The author has an hindex of 18, co-authored 49 publications receiving 2347 citations. Previous affiliations of Guolan Lu include The Wallace H. Coulter Department of Biomedical Engineering & Emory University.

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Medical hyperspectral imaging: a review

TL;DR: An overview of the literature on medical hyperspectral imaging technology and its applications is presented, an introduction for those new to the field, an overview for those working in the field and a reference for those searching for literature on a specific application are presented.
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Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review

TL;DR: This review provides a review of ultrasound-guided, breast biopsy and the fusion of ultrasound with other imaging modalities, especially magnetic resonance imaging (MRI), and discusses their future directions.
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Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging

TL;DR: A convolutional neural network classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI, and the CNN classification was validated by the manual annotation of a pathologist specialized in head and head cancer.
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Determination of Tumor Margins with Surgical Specimen Mapping Using Near-Infrared Fluorescence

TL;DR: It is demonstrated that fluorescence can be used as a sensitive and specific method of guiding surgeries for head and neck cancers and potentially other cancers with challenging imaging conditions, increasing the probability of complete resections and improving oncologic outcomes.
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Label-free reflectance hyperspectral imaging for tumor margin assessment: a pilot study on surgical specimens of cancer patients.

TL;DR: The feasibility of label-free, HSI for tumor margin assessment in surgical tissue specimens of H&N cancer patients is demonstrated and further development of the HSI technology is warranted for its application in image-guided surgery.