Abstract: An automated method for analyzing whether all cancerous or abnormal tissue has been removed as a result of surgical resection is disclosed. A number of tissue section slides are prepared representing all or a relatively large percentage of the tissue sample, and high-resolution digital microscopic images are formed of the sections. A clustering algorithm forms an image showing the healthy tissue margins, such representation being stored in a file of significantly smaller size than the original photograph. These two-dimensional image files may be formed into a three-dimensional image of the entire resected tissue, thereby improving the accuracy and ease by which a pathologist may determine if further surgery or radiation therapy, for example, are indicated.

Abstract: An automated method for analyzing whether all cancerous or abnormal tissue has been removed as a result of surgical resection is disclosed. A number of tissue section slides are prepared representing all or a relatively large percentage of the tissue sample, and high-resolution digital microscopic images are formed of the sections. A clustering algorithm forms an image showing the healthy tissue margins, such representation being stored in a file of significantly smaller size than the original photograph. These two-dimensional image files may be formed into a three-dimensional image of the entire resected tissue, thereby improving the accuracy and ease by which a pathologist may determine if further surgery or radiation therapy, for example, are indicated.