A review on a deep learning perspective in brain cancer classification
A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate
due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It …
due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It …
In-vivo and ex-vivo tissue analysis through hyperspectral imaging techniques: revealing the invisible features of cancer
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 …
capture much more information from a certain scene, both within and beyond the visual …
Intelligent ultra-light deep learning model for multi-class brain tumor detection
The diagnosis and surgical resection using Magnetic Resonance (MR) images in brain
tumors is a challenging task to minimize the neurological defects after surgery owing to the …
tumors is a challenging task to minimize the neurological defects after surgery owing to the …
Brain tumor classification using deep learning technique--a comparison between cropped, uncropped, and segmented lesion images with different sizes
Deep Learning is the newest and the current trend of the machine learning field that paid a
lot of the researchers' attention in the recent few years. As a proven powerful machine …
lot of the researchers' attention in the recent few years. As a proven powerful machine …
Deep Learning-Based Framework for In Vivo Identification of Glioblastoma Tumor using Hyperspectral Images of Human Brain
The main goal of brain cancer surgery is to perform an accurate resection of the tumor,
preserving as much normal brain tissue as possible for the patient. The development of a …
preserving as much normal brain tissue as possible for the patient. The development of a …
Supervised machine learning methods and hyperspectral imaging techniques jointly applied for brain cancer classification
Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-
ionizing as well as non-invasive. As a consequence, they have been extensively applied in …
ionizing as well as non-invasive. As a consequence, they have been extensively applied in …
[HTML][HTML] Surgical spectral imaging
Recent technological developments have resulted in the availability of miniaturised spectral
imaging sensors capable of operating in the multi-(MSI) and hyperspectral imaging (HSI) …
imaging sensors capable of operating in the multi-(MSI) and hyperspectral imaging (HSI) …
Hemorrhage detection based on 3D CNN deep learning framework and feature fusion for evaluating retinal abnormality in diabetic patients
Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and
accurate diagnosis can improve the analysis and prognosis of the disease. One of the …
accurate diagnosis can improve the analysis and prognosis of the disease. One of the …
Use of hyperspectral/multispectral imaging in gastroenterology. Shedding some–different–light into the dark
Hyperspectral/Multispectral imaging (HSI/MSI) technologies are able to sample from tens to
hundreds of spectral channels within the electromagnetic spectrum, exceeding the …
hundreds of spectral channels within the electromagnetic spectrum, exceeding the …
Non-invasive skin cancer diagnosis using hyperspectral imaging for in-situ clinical support
Skin cancer is one of the most common forms of cancer worldwide and its early detection its
key to achieve an effective treatment of the lesion. Commonly, skin cancer diagnosis is …
key to achieve an effective treatment of the lesion. Commonly, skin cancer diagnosis is …