Medical image analysis: progress over two decades and the challenges ahead

Abstract

ÐThe analysis of medical images has been woven into the fabric of the Pattern Analysis and Machine Intelligence (PAMI) community since the earliest days of these Transactions. Initially, the efforts in this area were seen as applying pattern analysis and computer vision techniques to another interesting dataset. However, over the last two to three decades, the unique nature of the problems presented within this area of study have led to the development of a new discipline in its own right. Examples of these include: the types of image information that are acquired, the fully three-dimensional image data, the nonrigid nature of object motion and deformation, and the statistical variation of both the underlying normal and abnormal ground truth. In this paper, we look at progress in the field over the last 20 years and suggest some of the challenges that remain for the years to come.

Application of automatic statistical post-processing method for analysis of ultrasonic and digital dermatoscopy images

“…The first signs of possibilities to use ROC curve analysis in medical decision-making tools were first suggested by Lusted [75–78]. After this, researches started to use this method in medical diagnostic [79–92] and medical imaging [93–103] aspects seeking to ensure faster diagnostic and save more lives of patients. In the last two decades, the ROC curve analysis is widely used in the field of dermatology [87–92].…”

Computer aided diagnosis in chest radiography

“…Articles describing techniques specifically designed for computerized detection of abnormalities in chest radiographs began to appear in the 1970s. These were among the first papers in the field of medical image analysis, as is noted in a review by Duncan and Ayache [64].…”

“…In a recent review concerning 20 years of research on medical image processing, Duncan and Ayache [64] cite work by Sklansky and Ballard [221] as their second reference, but it is also the only reference, out of 139, to work on the analysis of chest radiographs. Within the field of computer-aided diagnosis, mammography currently attracts far more attention and in this field a commercial product is on the market (ImageChecker by R2 Technology, Los Altos, CA).…”

What can bioinformatics do for Natural History museums?

“…It is very important to have a image analysis subsystem available. As commented above, there are now available many devices for acquiring images, ranging from the microscopic scale (electron microscope or light microscope with the use of digital cameras) up to the macroscopic scale (3-D acquisition systems like those used in Medical imaging -Duncan, 2000). All these images would be directly stored in the database repository, using standard processes to improve the speed of capture, and the quality of the images.…”