Ivan Cruz Aceves CIMAT

Databases for the Scientic Community

DCA1 - Database of 134 X-ray Coronary Angiograms in PGM format

The present database (DCA1) consists of 134 X-ray coronary angiograms, and their corresponding ground-truth image outlined by an expert cardiologist. Each angiogram is a 300 x 300 pixels, gray-scale image in pgm (Portable gray map) format.

Please cite the following paper:

Cervantes-Sanchez, Fernando, Ivan Cruz-Aceves, Arturo Hernandez-Aguirre, Martha Alicia Hernandez-Gonzalez, and Sergio Eduardo Solorio-Meza. 2019. "Automatic Segmentation of Coronary Arteries in X-ray Angiograms using Multiscale Analysis and Artificial Neural Networks" Applied Sciences 9, no. 24: 5507. https://doi.org/10.3390/app9245507
DOI: https://doi.org/10.3390/app9245507
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MTA18 - Dataset of 18 ground-truth images of Major Temporal Arcade in PGM format

The present database (MTA18) consists of 18 ground-truth images outlined by an expert ophthalmologist of the Major Temporal Arcade from the test set of DRIVE database of retinal fundus images. Each image is a 565 x 584 pixels, gray-scale image in pgm (Portable graymap) format.

Please cite the following paper:

Alvarado-Carrillo, Dora Elisa, Ivan Cruz-Aceves, Martha Alicia Hernández-González, and Luis Miguel López-Montero. 2022. "Robust Detection and Modeling of the Major Temporal Arcade in Retinal Fundus Images" Mathematics 10, no. 8: 1334.
DOI: https://doi.org/10.3390/math10081334
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Stenosis608 - Database of 608 images of Coronary Artery Stenosis in PGM format

The present database (Stenosis608) consists of 304 negative and 304 positive Coronary Artery Stenosis images, which were classified by an expert cardiologist. Each image is a 64 x 64 pixels, gray-scale image in pgm (Portable graymap) format.

Please cite the following paper:

Gil-Rios, Miguel-Angel, Ivan Cruz-Aceves, Arturo Hernandez-Aguirre, Martha-Alicia Hernandez-Gonzalez, and Sergio-Eduardo Solorio-Meza. 2024. "Improving Automatic Coronary Stenosis Classification Using a Hybrid Metaheuristic with Diversity Control" Diagnostics 14, no. 21: 2372. https://doi.org/10.3390/diagnostics14212372
DOI: https://doi.org/10.3390/diagnostics14212372
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Features473 - Dataset (csv) of 473 features computed from the positive and negative Coronary Stenosis images

The present dataset (Features473) consists of the 473 features computed from the 304 negative and 304 positive Coronary Artery Stenosis images. The dataset is a 473 x 608 table in csv format.