Diagnosis of animals stomach Cancer using Multiscale Convolutional Neural Network

Though incidences of stomach cancer in animals have decreased over the past several decades. The current study presents an innovative automated diagnosis classification method for Computed Tomography (CT). The use of image processing techniques and identifying patterns in the detection of animal stomach cancer from analyzing CT images with the multiscale convolution reduces human errors in detecting tumors, and speeds up diagnosis time. This study by using Multiscale CNN which presents CT picture to several deep CNN with different size and resolutions reaches to the diagnosis accuracy of ۹۴.۳±۰.۳ using multiscale convolution technique which reveals the efficiency proposed method.