Healthcare Computer Vision Lab
According to a 2016 estimation from IBM researchers, 90% of all Medical Big Data is imaging data.
Computer vision is a form of artificial intelligence where computers can “see” the world, analyze visual data and then make decisions from it or gain understanding about the environment and situation.
The Value of Computer Vision in Health Care
The widespread adoption of visual AI strategies for health care has only just begun. As a subfield of artificial intelligence, visual AI [computer vision] enables computers to "see" and process images and videos faster, more accurately, and more cost efficiently than a highly trained medical practitioner. Computer vision technology is quickly offering many benefits to the healthcare industry, such as:
- Accurate and efficient imaging analysis
- Smart operating rooms
- Better patient identification
- Increased healthcare safety
- Accelerated medical research
Redacted from: HIMSS
The Healthcare Computer Vision Program (HCVP) is comprised of the following people:
- Director: Ju Sun
- Co-Director: Chris Tignanelli
- Faculty: Tom Byrd
- Project Manager: Molly Diethelm
- Le Peng
- Tiancong Chen
- Hengyue Liang
Current key projects of the HCVP include:
- Diagnostic (Federated Learning) Rib Fracture
- Prognostic Rib Fracture
- Audiogram – Liang
- Tic Detection – Liang
- Liver US Detection – Chen
- Post-Extubation Dysphagia Prediction – Peng
- Hip Fracture – Chen
Peng L, Luo G, Walker A, Zaiman Z, Jones EK, Gupta H, Kersten K, Burns JL, Harle CA, Magoc T, Shickel B, Steenburg SD, Loftus T, Melton GB, Gichoya JW, Sun J, Tignanelli CJ. Evaluation of federated learning variations for COVID-19 diagnosis using chest radiographs from 42 US and European hospitals. J Am Med Inform Assoc. 2022 Dec 13;30(1):54-63. doi: 10.1093/jamia/ocac188. PMID: 36214629; PMCID: PMC9619688.
Loftus TJ, Ruppert MM, Shickel B, Ozrazgat-Baslanti T, Balch JA, Efron PA, Upchurch GR Jr, Rashidi P, Tignanelli C, Bian J, Bihorac A. Federated learning for preserving data privacy in collaborative healthcare research. Digit Health. 2022 Oct 27;8:20552076221134455. doi: 10.1177/20552076221134455. PMID: 36325438; PMCID: PMC9619858.
Sun J, Peng L, Li T, Adila D, Zaiman Z, Melton-Meaux GB, Ingraham NE, Murray E, Boley D, Switzer S, Burns JL, Huang K, Allen T, Steenburg SD, Gichoya JW, Kummerfeld E, Tignanelli CJ. Performance of a Chest Radiograph AI Diagnostic Tool for COVID-19: A Prospective Observational Study. Radiol Artif Intell. 2022 Jun 1;4(4):e210217. doi: 10.1148/ryai.210217. PMID: 35923381; PMCID: PMC9344211.