Deep learning in medical hyperspectral images: A review

R Cui, H Yu, T Xu, X Xing, X Cao, K Yan, J Chen - Sensors, 2022 - mdpi.com
With the continuous progress of development, deep learning has made good progress in the
analysis and recognition of images, which has also triggered some researchers to explore …

Hyperspectral imaging for early diagnosis of diseases: a review

H Mangotra, S Srivastava, G Jaiswal, R Rani… - Expert …, 2023 - Wiley Online Library
Hyperspectral Imaging (HSI) has grown to be one of the most crucial optical imaging
modalities with applications in numerous industries. The non‐invasive nature of HSI has led …

Trends in deep learning for medical hyperspectral image analysis

U Khan, S Paheding, CP Elkin… - IEEE Access, 2021 - ieeexplore.ieee.org
Deep learning algorithms have seen acute growth of interest in their applications throughout
several fields of interest in the last decade, with medical hyperspectral imaging being a …

Hyperspectral imaging for glioblastoma surgery: improving tumor identification using a deep spectral-spatial approach

F Manni, F van der Sommen, H Fabelo, S Zinger… - Sensors, 2020 - mdpi.com
The primary treatment for malignant brain tumors is surgical resection. While gross total
resection improves the prognosis, a supratotal resection may result in neurological deficits …

Automatic recognition of colon and esophagogastric cancer with machine learning and hyperspectral imaging

T Collins, M Maktabi, M Barberio, V Bencteux… - Diagnostics, 2021 - mdpi.com
There are approximately 1.8 million diagnoses of colorectal cancer, 1 million diagnoses of
stomach cancer, and 0.6 million diagnoses of esophageal cancer each year globally. An …

Review on the application of hyperspectral imaging technology of the exposed cortex in cerebral surgery

Y Wu, Z Xu, W Yang, Z Ning, H Dong - Frontiers in Bioengineering …, 2022 - frontiersin.org
The study of brain science is vital to human health. The application of hyperspectral imaging
in biomedical fields has grown dramatically in recent years due to their unique optical …

Discriminating healthy from tumor tissue in breast lumpectomy specimens using deep learning-based hyperspectral imaging

LJS Jong, N de Kruif, F Geldof, D Veluponnar… - Biomedical optics …, 2022 - opg.optica.org
Achieving an adequate resection margin during breast-conserving surgery remains
challenging due to the lack of intraoperative feedback. Here, we evaluated the use of …

[HTML][HTML] Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems

JH Leung, R Karmakar, A Mukundan, WS Lin, F Anwar… - Diagnostics, 2024 - mdpi.com
Brain cancer is a substantial factor in the mortality associated with cancer, presenting
difficulties in the timely identification of the disease. The precision of diagnoses is …

Estimating quantitative physiological and morphological tissue parameters of murine tumor models using hyperspectral imaging and optical profilometry

T Tomanic, L Rogelj, J Stergar, B Markelc… - Journal of …, 2023 - Wiley Online Library
Understanding tumors and their microenvironment are essential for successful and accurate
disease diagnosis. Tissue physiology and morphology are altered in tumors compared to …

[Retracted] Hyperspectral Image Analysis of Colon Tissue and Deep Learning for Characterization of Health care

A Akram Abdulrazzaq… - … and Public Health, 2022 - Wiley Online Library
Colon cancer is a disease characterized by the unusual and uncontrolled development of
cells that are found in the large intestine. If the tumour extends to the lower part of the colon …