Method and system for classification of endoscopic images using deep decision networks

US10482313B2 · kind B2 · utility

Assignee

• Siemens Healthcare Limited · DE

Inventors

• Venkatesh Murthy · Jamkhed, IN
• Vivek Singh · Monmouth Junction, US
• Shanhui Sun · Princeton, US
• Subhabrata Bhattacharya · Seattle, US
• Kai Ma · Plainsboro, US
• Ali Kamen · Skillman, US
• Bogdan Georgescu · Plainsboro, US
• Terrence Chen · Princeton, US
• Dorin Comaniciu · Princeton Junction, US

Key dates

• Filing date: Sep 29, 2016
• Grant date: Nov 19, 2019
• Expiry date: Dec 7, 2036

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H30/20
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method and system for classification of endoscopic images is disclosed. An initial trained deep network classifier is used to classify endoscopic images and determine confidence scores for the endoscopic images. The confidence score for each endoscopic image classified by the initial trained deep network classifier is compared to a learned confidence threshold. For endoscopic images with confidence scores higher than the learned threshold value, the classification result from the initial trained deep network classifier is output. Endoscopic images with confidence scores lower than the learned confidence threshold are classified using a first specialized network classifier built on a feature space of the initial trained deep network classifier.