PHT-bot: A deep learning based system for automatic risk stratification of COPD patients based upon signs of pulmonary hypertension

David Chettrit, Orna Bregman Amitai, Itamar Tamir, Amir Bar, Eldad Elnekave

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality worldwide. Identifying those at highest risk of deterioration would allow more effective distribution of preventative and surveillance resources. Secondary pulmonary hypertension is a manifestation of advanced COPD, which can be reliably diagnosed by the main Pulmonary Artery (PA) to Ascending Aorta (Ao) ratio. In effect, a PA diameter to Ao diameter ratio of greater than 1 has been demonstrated to be a reliable marker of increased pulmonary arterial pressure. Although clinically valuable and readily visualized, the manual assessment of the PA and the Ao diameters is time consuming and under-reported. The present study describes a non invasive method to measure the diameters of both the Ao and the PA from contrast-enhanced chest Computed Tomography (CT). The solution applies deep learning techniques in order to select the correct axial slice to measure, and to segment both arteries. The system achieves test Pearson correlation coefficient scores of 93% for the Ao and 92% for the PA. To the best of our knowledge, it is the first such fully automated solution.

Original languageEnglish
Title of host publicationMedical Imaging 2019
Subtitle of host publicationComputer-Aided Diagnosis
EditorsKensaku Mori, Horst K. Hahn
ISBN (Electronic)9781510625471
StatePublished - 2019
Externally publishedYes
EventMedical Imaging 2019: Computer-Aided Diagnosis - San Diego, United States
Duration: 17 Feb 201920 Feb 2019

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2019: Computer-Aided Diagnosis
Country/TerritoryUnited States
CitySan Diego


  • Chest Computed Tomography
  • Chronic Obstructive Pulmonary Disease
  • Computer Aided Diagnosis
  • Deep Learning
  • Pulmonary Hypertension


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