Automated Deep Learning Based Cardiac Quantification in Hypertrophic Cardiomyopathy: A Comparative Study with Manual Segmentation
Fully automated DL-based cardiac quantification provides accurate and reproducible assessment of the LV function, MR, and flow parameters in HCM patients, closely matching manual segmentation results. Incorporation of DL algorithms can substantially streamline the clinical workflow, although careful validation remains necessary in structurally complex cases such as HCM.
Authors
- Pranjal Phukan (ORCID: https://orcid.org/0000-0001-9210-0217)
- Deb Kumar Boruah (ORCID: https://orcid.org/0000-0003-3831-135X)
- Pranta Das (ORCID: https://orcid.org/0000-0003-2290-2200)
- Aishwarya Roshan (ORCID: https://orcid.org/0000-0002-5918-4735)
- Harshit Jain (ORCID: https://orcid.org/0009-0009-4281-6984)
- Kalyan Sarma (ORCID: https://orcid.org/0000-0002-4820-8279)
- Shivam Angiras (ORCID: https://orcid.org/0009-0000-3575-859X)
- Rajeev Bharadwaj (ORCID: https://orcid.org/0000-0003-2445-4181)
Institutions
- Gauhati Medical College and Hospital (IN)
- All India Institute of Medical Sciences Guwahati (IN)
Publication Details
- Journal
- Acta medica Lituanica
- Published
- 2025-08-11
- DOI
- https://doi.org/10.15388/amed.2025.32.2.8
- Primary Topic
- Cardiomyopathy and Myosin Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00