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Visual System

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

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Related Experiment Video

Updated: Jun 7, 2025

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

Computer Vision in Digital Neuropathology.

Cong Cong^1,2,3, Sidong Liu^4,5, Antonio Di Ieva^5,6,7,8

¹School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia. thomas.cong@mq.edu.au.

Advances in Experimental Medicine and Biology

|November 10, 2024

Summary

This summary is machine-generated.

Computer vision and pathomics enhance digital neuropathology for faster, precise diagnostics. These technologies aid in early disease detection, brain tumor classification, and biomarker assessment, improving patient care.

Keywords:

Computational histopathology Computational neuropathology Computer vision Digital neuropathology Image classification Pathomics Stain normalization

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Area of Science:

Neuropathology
Medical Imaging
Computer Vision

Background:

Digital pathology transforms neuropathology with rapid, precise tissue analysis.
Computer vision and pathomics are crucial for automating diagnostics and extracting insights from neuropathological images.

Purpose of the Study:

To explore computer vision's role in integrating traditional and digital neuropathology.
To provide a comprehensive overview of computer vision applications in neuropathology.

Main Methods:

Image preprocessing techniques.
Computer vision algorithms for diagnostic decision support.
Quantitative analysis of tissue biomarkers.

Main Results:

Computer vision aids in early detection of neurological disorders.
Automated classification of brain tumors.
Quantitative assessment of tissue biomarkers.

Conclusions:

Computer vision bridges traditional and digital neuropathology, enhancing diagnostic accuracy and efficiency.
Integration of digital pathology and computer vision offers significant opportunities for neurosurgical practice and research.