Major Congratulations to Dr. Muhammad Imran, Postdoctoral Associate in the Department of Medicine and Dr. Jonathan R. Krebs, General Surgery Resident in the Department of Vascular Surgery at the University of Florida. Their co-authored paper, “Volumetric Analysis of Acute Uncomplicated Type B Aortic Dissection Using an Automated Deep Learning Aortic Zone Segmentation Model.” has been officially accepted and published in the esteemed Journal of Vascular Surgery (JVS). The JVS’s latest prospective impact factor of 4.4 and acceptance rate of 5.3%, highlight the prestige of their papers’ concept, as well as the rigor it must have taken to publish with such promising results.
Their development of a deep learning model to analyze volumetric growth in patients with medically managed acute uncomplicated type B aortic dissection (auTBAD) is one that has never been published on in the past. The novel concept to develop a framework capable of assisting clinicians with disease progression is one with substantial implications not only in the aortic segmentation space, but also for the field of medical imaging as a whole. Additionally, the contributions of this work have significant capabilities to increase patient outcomes for those suffering from auTBAD.
The acceptance of this paper by the Journal of Vascular Surgery underscores its scientific rigor and potential impact. This recognition is not only a personal milestone for Dr. Imran and his co-author but also serves as testament to their dedication for advancing current medical imaging capabilities for improved patient outcomes.