Comprehensive Survey on: Hybrid Model for A  Detection of Various Types of Heart Diseases  using Deep Learning Techniques

Author(s)	Ms. Mithuna B N, Dr. Pushpa Ravikumar
Country	India
Abstract	Nowadays, heart diseases are among the top causes of death around the world. ECG signals, CT scan images, and MRIs have become more popular in recent years for detecting heart diseases. Image processing helps with preprocessing images of heart diseases. This leads to improvements in diagnosing illnesses accurately. When dealing with a large amount of images, radiologists rely on accuracy in preprocessing heart diseases. The heart is a very important muscle in our body, roughly the size of a fist.. It acts as the body’s central pump, circulating blood, oxygen, and nutrients through the circulatory system to all tissues and organs while removing waste like carbon dioxide. To detect heart diseases, data collection, noise removal, normalization, and edge detection are used on inputs such as ECG signals, CT scan images, MRIs, and extracting morphological features from the input images.
Keywords	Image acquisition, Noise Removal Technique, Analysis of Signals and Morphological Feature Extraction and Classification.
Field	Computer > Data / Information
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-06-04
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.80310

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