Study of Detection Analysis of Cardiac Amyloidosis Heart Disease Using Image Segmentation Technique

Study of Detection Analysis of Cardiac Amyloidosis Heart Disease Using Image Segmentation Technique Gladys Jebakumari Arun Raaza Abstract Cardiac amyloidosis is a collection of mayhem, which increases the less important disposition of abnormal proteins in the heart. It may happen either in segregation or like a fraction of systemic disease and can be hereditary or attained. The major forms of amyloid proteins, namely Amyloid Light Chain also Amyloid Transthyretin (ATTR), can penetrate the heart. With the enhanced utilization of advanced image techniques and procedures, the identification and diagnosis of cardiac amyloidosis, especially ATTR, has become very easier. In general, congestive heart failure disease has been diagnosed through an electrocardiogram. In this survey, the ultrasound heart image is gathered as an input image to diagnose whether the heart’s functioning is normal or abnormal. Based on input ultrasound heart image or picture, the ultrasound high-frequency sound waves afford the heart’s image and valves, which allows us to observe the heart-pumping action. The image segmentation technique was well performed in segmenting the specified heart image into high-intensity range, and low-intensity level deliberated to enhance patients’ lives with cardiac amyloidosis. The disorders or variations or any abnormalities happening in the heart can be done via a segmentation approach through that intensity level. 07 01 2021 042021 http://dx.doi.org/10.1088/crossmark-policy iopscience.iop.org Study of Detection Analysis of Cardiac Amyloidosis Heart Disease Using Image Segmentation Technique Journal of Physics: Conference Series paper Published under licence by IOP Publishing Ltd http://creativecommons.org/licenses/by/3.0/ https://iopscience.iop.org/info/page/text-and-data-mining 10.1088/1742-6596/1964/4/042021 https://iopscience.iop.org/article/10.1088/1742-6596/1964/4/042021 https://iopscience.iop.org/article/10.1088/1742-6596/1964/4/042021/pdf https://iopscience.iop.org/article/10.1088/1742-6596/1964/4/042021/pdf https://iopscience.iop.org/article/10.1088/1742-6596/1964/4/042021 https://iopscience.iop.org/article/10.1088/1742-6596/1964/4/042021/pdf Kyriakou 10.1186/s12872-018-0952-8 Diagnosis of Cardiac Amyloidosis: a systematic review on the role of imaging and biomarkers European journal of nuclear medicine and molecular imaging Kircher 46 1407 2019 10.1007/s00259-019-04290-y Detection of cardiac amyloidosis with 18 F-Florbetaben-PET/CT compared to echocardiography, cardiac MRI, and DPD-scintigraphy Bella 2014 10.1093/ehjci/jeu158 The mosaic of the cardiac amyloidosis diagnosis: role of imaging in subtypes and stages of the disease The International Journal of Cardiovascular Imaging Rausch 37 81 2021 10.1007/s10554-020-01948-9 Left atrial strain imaging differentiates cardiac amyloidosis and hypertensive heart disease Tuzovic 2017 10.1007/s11912-017-0607-4 Cardiac Amyloidosis: Diagnosis and Treatment Strategies Nicolosi 2014 Prospective identification of patients with amyloid heart disease by two-dimensional echocardiography Subbiah 2014 Reduction of Noises in ECG Signal by Various Filters Cardiovascular Imaging Dorbala 13 1368 2020 How to image cardiac amyloidosis: a practical approach Kittleson 2020 10.1161/CIR.0000000000000792 Cardiac Amyloidosis: Evolving Diagnosis and Management A Scientific Statement From the American Heart Association Circulation Maceira 111 186 2005 10.1161/01.CIR.0000152819.97857.9D Cardiovascular magnetic resonance in cardiac amyloidosis Cristina Quarta 2012 Cardiac Amyloidosis Perry 2019 10.1016/j.hlc.2019.04.017 Echocardiography in Infiltrative Cardiomyopathy Periodicals of Engineering and Natural Sciences Sathish Kumar 6 2018 Study and Analysis of Intrusion Detection System Using Random Forest and Linear Regression