Imagen’s FDA-cleared AI software, FractureDetect, designed to detect fractures in musculoskeletal radiographs, improves clinicians’ accuracy at diagnosing fractures. Clinical testing showed that both clinicians with extensive training in musculoskeletal imaging and clinicians with limited training in musculoskeletal imaging were significantly more accurate when assisted by FractureDetect.
Raise The Bar For Diagnostic Accuracy
Imagen’s proprietary Artificial Intelligence (AI) software empowers physicians with immediate, accurate results and enables comprehensive diagnostic reports.
Imagen Does More
While other institutions rely on resumes and handshakes, Imagen verifies actual diagnostic capabilities with a multi-hour image-based evaluation. Our medical leadership is focused on finding the best diagnosticians, not the loftiest pedigree.
Select Medical Leadership
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Howard Kessler, MD
Head of Medical Group
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Serge Sicular, MD
Medical Director
Howard Kessler, MD
Head of Medical Group
Howard Kessler, MD, is the Head of Medical Group at Imagen. Prior to joining Imagen, Dr. Kessler was a radiologist and, prior to that, Chairman of Radiology at CarePoint Health System. He is a former Director of Diagnostic Imaging at Fox Chase Medical Center. He has extensive experience in quality assurance and performance improvement, having served as Medical Director for Radiology at a regional insurance company. He has also served as a business consultant to various radiology practices and been involved as a shareholder or managing partner in numerous companies and practices, including Radiology Reimbursement Solutions (1999-2010) and New Jersey Imaging Associates (2008–2014). He attended medical school at Ohio State University; interned at Riverside Methodist Hospital; completed his residency at University of Pennsylvania Department of Radiology, where he was Chief Resident; and completed a fellowship in gastrointestinal radiology at University Hospital, Lund, Sweden.
Serge Sicular, MD
Medical Director
Serge Sicular, MD, is the current Director of Emergency Imaging at the Mount Sinai Health System, overseeing the imaging from the emergency rooms at the Mount Sinai, Mount Sinai Queens, Beth Israel, Kings Highway, St. Luke’s, and Mount Sinai West hospitals in New York City. He is also an assistant professor and course director at the Icahn School of Medicine at Mount Sinai. He is a graduate of the Sackler Medical School in Tel Aviv with honors. He completed his internship at the Saint Barnabas Medical Center and completed his residency in radiology at Mount Sinai, where he also served as president of the Mount Sinai housestaff and was on the medical board and administrative executive committee for the hospital.
Human-Powered Machine Learning
Imagen’s proprietary, FDA-cleared Machine Learning software immediately detects and documents findings, allowing for diagnosis and treatment in a single, seamless patient visit.
Automated Reports
Automated preliminary results allow customer physicians to immediately transact on results and allow Imagen’s U.S. based, board-certified specialists to deliver high-quality final reports.
Fulfill Quadruple Aim of Healthcare
Higher Quality
Improve accuracy, with FDA clinical trial results for Imagen’s chest X-ray software reducing clinician misses of life-threatening cases by 73%.
Lower Cost
Documentation allows for early intervention and ruling out ER visits, which reduce subsequent hospital admissions.
Patient Experience
38% of patients reported having anxiety while waiting for imaging results. Imagen is changing this by significantly reducing the wait time for all imaging results.
Clinician Experience
EMR integration allows immediate, automatic sync with patient clinical record; more confident diagnoses and improved ability to provide timely care.
Published Studies
At Imagen, we are working to change how diagnostics are delivered. The following are peer-reviewed publications written by us about the current and future state of imaging diagnostics
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Imagen’s FDA-cleared AI software, Chest-CAD, designed to detect suspicious regions of interest in chest radiographs, highlighted a region of a chest X-ray that was previously missed during unaided interpretation. This case shows that additional information provided by Imagen’s AI software was able to detect a life threatening finding.
Imagen developed an AI software designed to detect fractures across multiple anatomical areas throughout the musculoskeletal system. A multi-site study showed the AI software, referred to as a deep learning system, accurately identified fractures throughout the adult musculoskeletal system. The results were used in part to support FDA clearance of Imagen’s software (FractureDetect) which now assists clinicians in detecting fractures for the subset of the anatomic regions reported in this paper.
Imagen developed an AI software designed to detect and localize fractures in wrist radiographs. A rigorous clinical study showed that the clinicians utilizing the AI software, referred to as a deep learning model, had a 47% relative reduction in misinterpretations. The significant improvement in diagnosing fractures shows that information provided by Imagen’s AI software can substantially enhance physician accuracy.