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Updated: Jul 19, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

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半监督的3D视网膜液体细分通过相关联的相互学习与全球推理注意力.

Kaizhi Cao1, Yi Liu2, Xinhao Zeng1

  • 1School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Biomedical optics express
|December 16, 2024
PubMed
概括

这项研究引入了一种新的半监督方法,用于在光学连贯性断层扫描 (OCT) 中对3D液体病变进行细分,以诊断糖尿病黄斑 (DME). 该方法通过利用相关性相互学习和注意力机制来提高准确性,优于现有方法.

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相关概念视频

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
Three-Dimensional Microscopy in Microbiology01:28

Three-Dimensional Microscopy in Microbiology

Three-dimensional imaging techniques are essential in cell biology, allowing researchers to visualize intricate cellular structures with high resolution. Two prominent methods, Differential Interference Contrast Microscopy (DIC) and Confocal Scanning Laser Microscopy (CSLM), provide distinct advantages for imaging live and thick specimens, respectively.Differential Interference Contrast MicroscopyDIC microscopy enhances contrast in transparent, unstained samples by converting phase...