|Title:||Surgical aid visualization system for glioblastoma tumor identification based on deep learning and in-vivo hyperspectral images of human patients||Authors:||Fabelo Gómez, Himar Antonio
Ortega Sarmiento, Samuel
Sarmiento Rodríguez, Roberto
Marrero Callicó, Gustavo Iván
|Editors:||Linte, Cristian A.
|UNESCO Clasification:||3314 Tecnología médica||Keywords:||Brain Shift
Cancer Surgery, et al
|Issue Date:||2019||Journal:||Progress in Biomedical Optics and Imaging - Proceedings of SPIE||Conference:||Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling||Abstract:||Brain cancer surgery has the goal of performing an accurate resection of the tumor and preserving as much as possible the quality of life of the patient. There is a clinical need to develop non-invasive techniques that can provide reliable assistance for tumor resection in real-time during surgical procedures. Hyperspectral imaging (HSI) arises as a new, noninvasive and non-ionizing technique that can assist neurosurgeons during this difficult task. In this paper, we explore the use of deep learning (DL) techniques for processing hyperspectral (HS) images of in-vivo human brain tissue. We developed a surgical aid visualization system capable of offering guidance to the operating surgeon to achieve a successful and accurate tumor resection. The employed HS database is composed of 26 in-vivo hypercubes from 16 different human patients, among which 258,810 labelled pixels were used for evaluation. The proposed DL methods achieve an overall accuracy of 95% and 85% for binary and multiclass classifications, respectively. The proposed visualization system is able to generate a classification map that is formed by the combination of the DL map and an unsupervised clustering via a majority voting algorithm. This map can be adjusted by the operating surgeon to find the suitable configuration for the current situation during the surgical procedure.||URI:||http://hdl.handle.net/10553/58307||ISBN:||9781510625495||ISSN:||1605-7422||DOI:||10.1117/12.2512569||Source:||Progress in Biomedical Optics and Imaging - Proceedings of SPIE [ISSN 1605-7422], v. 10951, 1095110|
|Appears in Collections:||Artículos|
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