Multi-constraints based deep learning model for automated segmentation and diagnosis of coronary artery disease in X-ray angiographic images

Mona Algarni; Abdulkader Al-Rezqi; Faisal Saeed; Abdullah Alsaeedi; Fahad Ghabban

Multi-constraints based deep learning model for automated segmentation and diagnosis of coronary artery disease in X-ray angiographic images

Mona Algarni, Abdulkader Al-Rezqi, Faisal Saeed, Abdullah Alsaeedi, Fahad Ghabban

Research output: Contribution to journal › Article › peer-review

15 Citations (SciVal)

Original language	English
Journal	Peerj Computer Science
Volume	8
Publication status	Published (VoR) - 3 Jun 2022

Keywords

X-ray angiography
Noise removal
Coronary artery disease
Segmentation
Classification
Attention-based nested U-Net
VGG-16

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https://peerj.com/articles/cs-993/

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@article{aa842365f50a4b188ed52bfd4fed1189,

title = "Multi-constraints based deep learning model for automated segmentation and diagnosis of coronary artery disease in X-ray angiographic images",

keywords = "X-ray angiography, Noise removal, Coronary artery disease, Segmentation, Classification, Attention-based nested U-Net, VGG-16",

author = "Mona Algarni and Abdulkader Al-Rezqi and Faisal Saeed and Abdullah Alsaeedi and Fahad Ghabban",

year = "2022",

month = jun,

day = "3",

language = "English",

volume = "8",

journal = "Peerj Computer Science",

issn = "2376-5992",

publisher = "PeerJ",

}

TY - JOUR

T1 - Multi-constraints based deep learning model for automated segmentation and diagnosis of coronary artery disease in X-ray angiographic images

AU - Algarni, Mona

AU - Al-Rezqi, Abdulkader

AU - Saeed, Faisal

AU - Alsaeedi, Abdullah

AU - Ghabban, Fahad

PY - 2022/6/3

Y1 - 2022/6/3

KW - X-ray angiography

KW - Noise removal

KW - Coronary artery disease

KW - Segmentation

KW - Classification

KW - Attention-based nested U-Net

KW - VGG-16

M3 - Article

SN - 2376-5992

VL - 8

JO - Peerj Computer Science

JF - Peerj Computer Science

ER -

Multi-constraints based deep learning model for automated segmentation and diagnosis of coronary artery disease in X-ray angiographic images

Keywords

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