The evidence says that liver disease detection using CAD is one of the most
efficient techniques but the presence of better organization of studies and the
performance parameters to represent the result analysis of the proposed
techniques are pointedly missing in most of the recent studies. Few benchmarked
studies have been found in some of the papers as benchmarking makes a reader
understand that under which circumstances their experimental results or
outcomes are better and useful for the future implementation and adoption of
the work. Liver diseases and image processing algorithms, especially in
medicine, are the most important and important topics of the day.
Unfortunately, the necessary data and data, as they are invoked in the
articles, are low in this area and require the revision and implementation of
policies in order to gather and do more research in this field. Detection with
ultrasound is quite normal in liver diseases and depends on the physician's
experience and skills. CAD systems are very important for doctors to understand
medical images and improve the accuracy of diagnosing various diseases. In the
following, we describe the techniques used in the various stages of a CAD
system, namely: extracting features, selecting features, and classifying them.
Although there are many techniques that are used to classify medical images, it
is still a challenging issue for creating a universally accepted approach.
Behnam Kiani Kalejahi, Saeed Meshgini, Sabalan Daneshvar, Shiva Asadzadeh