In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to
capture much more information from a certain scene, both within and beyond the visual …

The use of hyperspectral imaging for medical applications is becoming more common in
recent years. One of the main obstacles that researchers find when develo** …

Background Hyperspectral imaging (HSI) has the potential to enhance surgical tissue
detection and diagnostics. Definite utilization of intraoperative HSI guidance demands …

Neuro-oncological surgery is the primary brain cancer treatment, yet it faces challenges with
gliomas due to their invasiveness and the need to preserve neurological function. Hence …

Significance Accurate identification between pathologic (eg, tumors) and healthy brain
tissue is a critical need in neurosurgery. However, conventional surgical adjuncts have …

Service-continuity in distributed computing can be enhanced by designing self-organized
systems, with a non-fixed structure, able to modify their structure and organization, as well as …

Several causes make brain cancer identification a challenging task for neurosurgeons
during the surgical procedure. The surgeons' naked eye sometimes is not enough to …

Medical image segmentation demonstrates a significant part in curative image exploration
and dispensation, is a multifaceted and perplexing assignment for reckoning efficiency and …

This article presents the optimization and hybrid parallelization of a spatial–spectral feature
extraction (FE) method from hyperspectral images (HSIs) using local covariance matrix (CM) …

Surgery for gliomas (intrinsic brain tumors), especially when low-grade, is challenging due
to the infiltrative nature of the lesion. Currently, no real-time, intra-operative, label-free and …