In an information-intensive culture, computer technology has begun to reach other conventionally realizable sectors. Alongside this trend, several high-tech machines have emerged. Concurrently, a variety of high-tech devices have emerged in the traditional medical area in order to aid physicians in the treatment process. The introduction of sophisticated picture recognition technology has decreased a significant amount of the doctor's effort required to evaluate the tiny sick cells within the human body. The modernization, rationalization, and intelligence of the design and production of illness detection equipment utilizing image extraction technologies are increasing. In the medical industry, feature-based image recognition technology disease diagnosis equipment analyses and diagnoses pathology using picture collecting. From 2018 to 2022, the current study examines several image extraction algorithms applied to the identification of canine illnesses. Using classification, researchers have reached a high level of sensitivity and specificity in medical picture analysis. This evaluation not only identifies obstacles, but also identifies and presents fresh research prospects for this field's scholars