ArticleProceedings of SPIE--the International Society for Optical Engineering
Thyroid Carcinoma Detection on Whole Histologic Slides Using Hyperspectral Imaging and Deep Learning.
Article in Proceedings of SPIE--the International Society for Optical Engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Portable Multispectral Optoelectronic System for Thyroid Cancer Detection.Sensors (Basel, Switzerland) · 2026Article
- A spatial-spectral vision transformer model for head and neck cancer detection with hyperspectral, RGB, and synthesized RGB histologic images.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Optimization of Transfer Learning of Foundation Models for Hyperspectral Histologic Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- A high-speed hyperspectral imaging system and large-scale hyperspectral dataset for abdominal surgical applications.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- An automatic processing framework for hyperspectral histologic images and benchmark dataset.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Dye amount quantification of Papanicolaou-stained cytological images by multispectral unmixing: spectral analysis of cytoplasmic mucin.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Detection and margin assessment of thyroid carcinoma with microscopic hyperspectral imaging using transformer networks.Journal of biomedical optics · 2024Article
- Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.Journal of biomedical optics · 2024Article
- Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma.Journal of biomedical optics · 2024Article
- A Video Transformer Network for Thyroid Cancer Detection on Hyperspectral Histologic Images.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Extended Depth of Field Imaging for Mosaic Hyperspectral Images.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Conditional Generative Adversarial Network (cGAN) for Synthesis of Digital Histologic Images from Hyperspectral Images.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Trends in AI-powered Classification of Thyroid Neoplasms Based on Histopathology Images - a Systematic Review.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2023Article
- Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging.Journal of biomedical optics · 2022Article
- An automatic whole-slide hyperspectral imaging microscope.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
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5 authors.
Funding
Abstract
Hyperspectral imaging (HSI), a non-invasive imaging modality, has been successfully used in many different biological and medical applications. One such application is in the field of oncology, where hyperspectral imaging is being used on histologic samples. This study compares the performances of different image classifiers using different imaging modalities as training data. From a database of 33 fixed tissues from head and neck patients with follicular thyroid carcinoma, we produced three different datasets: an RGB image dataset that was acquired from a whole slide image scanner, a hyperspectral (HS) dataset that was acquired with a compact hyperspectral camera, and an HS-synthesized RGB image dataset. Three separate deep learning classifiers were trained using the three datasets. We show that the deep learning classifier trained on HSI data has an area under the receiver operator characteristic curve (AUC-ROC) of 0.966, higher than that of the classifiers trained on RGB and HSI-synthesized RGB data. This study demonstrates that hyperspectral images improve the performance of cancer classification on whole histologic slides. Hyperspectral imaging and deep learning provide an automatic tool for thyroid cancer detection on whole histologic slides.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.