相关实验视频
Updated: Aug 17, 2026

10:25
Deep Learning-Based Segmentation of Cryo-Electron Tomograms
Published on: November 11, 2022
8.9K
人类选择偏差驱动着更基本的真相效应的线性性质,在可解释的深度学习中,光学连贯性断层扫描图像分割的线性性质
Peter M Maloca1,2,3, Maximilian Pfau1,2,4, Lucas Janeschitz-Kriegl1,2
1Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland.
Journal of biophotonics
|October 5, 2023
概括
医疗图像分析的深度学习 (DL) 模型,如光学连贯性断层扫描 (OCT),随着更多标记数据的增加而得到改善. 增加地面真相数据大小和分级器可以提高DL的性能,减轻人类对注释的偏见.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 监督深度学习 (DL) 模型需要广泛的,准确注释的训练数据,通常来自人类评分员.
- 医学成像中的人类注释,例如光学连贯断层扫描 (OCT),可以引入不准确和偏见.
- 地面真相数据的质量和数量显著影响DL模型性能.
研究的目的:
- 调查地面真相数据大小和人类分级器数量对DL预测性能的影响.
- 在不同的数据条件下评估DL系统的一致性和自我改进能力.
- 量化基本事实模糊性和更大的数据集的好处之间的关系.
主要方法:
- 在各种实验中使用一致的DL架构,具有不同的训练数据集大小和人类评级人员数量.
- 每个试验条件重复三次以确保可靠性.
- 分析了DL预测性能与基本真相大小,分级变化和数据模两可的关系.
主要成果:
- 最大的培训数据集产生了与人类专家可比的DL性能.
- DL系统表现出很高的一致性,但表现不佳的模型在重新培训后并没有自主改善.
- 在基准真相模糊性和更大的数据集的积极影响 ("更多的基准真相效应") 之间确定了线性关系.
结论:
- 增加注释训练数据的大小对于提高DL在医学图像分析中的性能至关重要.
- 基本真相模糊性是一个挑战,可以通过增加数据集大小来部分克服.
- 这些发现强调了数据数量和质量的重要性,在为海外国家和地区和类似应用开发可靠的DL模型.
相关概念视频
Vision
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
Classification of Systems-I
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Linear time-invariant Systems
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
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.
Gestalt Principles of Perception
Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
Perceptual Constancy
Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...

