Cancer detection from stained biopsies using high-speed spectral imaging

Cancer detection from stained biopsies using high-speed spectral imaging

Show other versions (1)

The escalating demand for diagnosing pathological biopsies requires the procedures to be expedited and automated. The existing imaging systems for measuring biopsies only measure color, and even though a lot of effort is invested in deep learning analysis, there are still serious challenges regardin...

Full description

Bibliographic Details
Main Authors: Barshack, I. (Author), Bronshtein-Berger, I. (Author), Brozgol, E. (Author), Garini, Y. (Author), Gondra, H. (Author), Kumar, P. (Author), Lindner, M. (Author), Medalion, S. (Author), Necula, D. (Author), Shapira, Y. (Author), Twito, L. (Author)
Format: Article
Language:English
Published: Optica Publishing Group (formerly OSA) 2022
Subjects:
4',6 diamidino 2 phenylindole
aneuploidy
Article
artificial intelligence
Biopsy
breast cancer
bright field microscopy
Cancer detection
cancer diagnosis
cancer grading
cell differentiation
classification algorithm
Classification algorithm
Color information
controlled study
convolutional neural network
deep learning
Deep learning
diagnostic test accuracy study
Diseases
DNA extraction
female genital tract tumor
Fourier transform mass spectrometry
High Speed
histopathology
human
human tissue
hyperspectral imaging
image analysis
Image enhancement
image quality
interferometry
learning algorithm
malignant neoplasm
mean squared error
measurement accuracy
Medical imaging
Medical settings
patient care
Patient treatment
Performance
scanning electron microscopy
sensitivity and specificity
Spectral classification
Spectral images
Spectral imaging
Spectral information
Spectroscopy
tumor biopsy
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items