Abstract
The main purpose of a medical image is to provide information to a human reader, such as a radiologist, so that a diagnosis can be reached — rather than to display the beauty of the human internal workings. It is important to understand how the human visual system affects the perception of contrast and spatial resolution of structures that are present in the image. If the image is not properly displayed, or the environment is not appropriate, subtle clinical signs may go unnoticed, which can potentially lead to a misdiagnosis. This chapter provides an introduction to human visual perception and task based objective assessment of an imaging system. A model for the contrast sensitivity of the human visual system is presented. This model is used to derive the greyscale standard display function for medical displays. Task based assessment measures the quality of an imaging system as the ability of an observer to perform a well defined task, based on a set of images. Metrics for observer performance are introduced, as well as experimental methodologies for the measurement of human performance. The last section of the chapter describes the estimation of task performance based on mathematical observer models.
Reiser, I.
[1]
- University of Chicago, Chicago (United States)
Citation Formats
Reiser, I.
Image Perception and Assessment. Chapter 18.
IAEA: N. p.,
2014.
Web.
Reiser, I.
Image Perception and Assessment. Chapter 18.
IAEA.
Reiser, I.
2014.
"Image Perception and Assessment. Chapter 18."
IAEA.
@misc{etde_22360641,
title = {Image Perception and Assessment. Chapter 18}
author = {Reiser, I.}
abstractNote = {The main purpose of a medical image is to provide information to a human reader, such as a radiologist, so that a diagnosis can be reached — rather than to display the beauty of the human internal workings. It is important to understand how the human visual system affects the perception of contrast and spatial resolution of structures that are present in the image. If the image is not properly displayed, or the environment is not appropriate, subtle clinical signs may go unnoticed, which can potentially lead to a misdiagnosis. This chapter provides an introduction to human visual perception and task based objective assessment of an imaging system. A model for the contrast sensitivity of the human visual system is presented. This model is used to derive the greyscale standard display function for medical displays. Task based assessment measures the quality of an imaging system as the ability of an observer to perform a well defined task, based on a set of images. Metrics for observer performance are introduced, as well as experimental methodologies for the measurement of human performance. The last section of the chapter describes the estimation of task performance based on mathematical observer models.}
place = {IAEA}
year = {2014}
month = {Sep}
}
title = {Image Perception and Assessment. Chapter 18}
author = {Reiser, I.}
abstractNote = {The main purpose of a medical image is to provide information to a human reader, such as a radiologist, so that a diagnosis can be reached — rather than to display the beauty of the human internal workings. It is important to understand how the human visual system affects the perception of contrast and spatial resolution of structures that are present in the image. If the image is not properly displayed, or the environment is not appropriate, subtle clinical signs may go unnoticed, which can potentially lead to a misdiagnosis. This chapter provides an introduction to human visual perception and task based objective assessment of an imaging system. A model for the contrast sensitivity of the human visual system is presented. This model is used to derive the greyscale standard display function for medical displays. Task based assessment measures the quality of an imaging system as the ability of an observer to perform a well defined task, based on a set of images. Metrics for observer performance are introduced, as well as experimental methodologies for the measurement of human performance. The last section of the chapter describes the estimation of task performance based on mathematical observer models.}
place = {IAEA}
year = {2014}
month = {Sep}
}