Application of deep learning for medical imaging evaluation

Abstract

This disclosure generally pertains to methods and systems for processing electronic data obtained from imaging or other diagnostic and evaluative medical procedures. Certain embodiments relate to methods for the development of deep learning algorithms that perform machine recognition of specific features and conditions in imaging and other medical data. Another embodiment provides systems configured to detect and localize medical abnormalities on medical imaging scans by a deep learning algorithm.

Description

[0001] related application [0002] This application claims the benefit of priority from Indian Patent Application No. 201821042894 filed on November 14, 2018, which is hereby incorporated by reference in its entirety for all purposes. technical field [0003] The present disclosure generally relates to methods and systems for processing electronic data obtained from imaging or other diagnostic and evaluation medical procedures. Some embodiments relate to methods for the development of deep learning algorithms that perform machine recognition of specific features and conditions in imaging and other medical data. Background technique [0004] Medical imaging techniques such as computed tomography (CT) and X-ray imaging are widely used in diagnosis, clinical research and treatment planning. There is an emerging need for automated methods that improve the efficiency, accuracy, and cost-effectiveness of medical imaging assessments. [0005] Non-contrast head CT scans are among...

AI Technical Summary

Problems solved by technology

The training and validation datasets for most studies had <200 head CT scans, raising concerns about the robustness of these algorithms

Furthermore, there is no standard public head CT dataset to directly compare the performance of algorithms

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