Deep Belief Bayesian Joint Conditional Detection of coronary artery plaque and stenosis in X-ray angiography images
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-19428-w.pdf
Reference20 articles.
1. Cong C, Kato Y, Vasconcellos HDD, Ostovaneh MR, Lima JAC, Ambale-Venkatesh B (2023) Deep learning-based end-to-end automated stenosis classification and localization on catheter coronary angiography. Front Cardiovasc Med 10:944135. https://doi.org/10.3389/fcvm.2023.944135
2. Domenico De Santis, Tiziano Polidori, Giuseppe Tremamunno, Carlotta Rucci, Giulia Piccinni, Marta Zerunian, Luca Pugliese, Antonella Del Gaudio, Gisella Guido, Luca Barbato, Andrea Laghi, Damiano Caruso (2023) Deep learning image reconstruction algorithm: impact on image quality in coronary computed tomography angiography. La radiologia medica. Springer. [Deep Learning Image Reconstruction (DLIR)]
3. Jong Hak Moon, Da Young Lee, Won Chul Cha, Myung Jin Chung, Kyu-Sung Lee, Baek Hwan Cho, Jin Ho Choi (2020) Automatic stenosis recognition from coronary angiography using convolutional neural networks. Computer Methods and Programs in Biomedicine. Elsevier
4. Jiang Z, Ou C, Rehan R, Yong A (2021) Coronary vessel segmentation using multiresolution and multiscale deep learning. Informatics in Medicine Unlocked. Elsevier. https://doi.org/10.1016/j.imu.2021.100602
5. Miguel Nobre Menezes, João Lourenc¸o-Silva, Beatriz Silva, Tiago Rodrigues, Ana Rita G. Francisco, Pedro Carrilho Ferreira, Arlindo L. Oliveira, Fausto J. Pintoa (2022) Development of deep learning segmentation models for coronary X-ray angiography: Quality assessment by a new global segmentation score and comparison with human performance. Revista Portuguesa de Cardiologia. Springer
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