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2020 – today
- 2024
[c9]Felicia Alfano, David Bermejo-Peláez, Lucilio Cordero-Grande, Karla Ferreres García, Juan Enrique Ortuño Fisac, Oscar Bueno Zamora, Serafín Lizarraga, Andrés Santos, Javier Pascau, María J. Ledesma-Carbayo:
Learning Breast Tissue Prone-To-Supine Displacement for Surgical Planning with Convolutional Neural Networks. ISBI 2024: 1-5- [c8]Roberto Mancebo-Martín, Lin Lin
, Elena Dacal, Miguel A. Luengo-Oroz, David Bermejo-Peláez:
How many labels do I need? self-supervised learning strategies for multiple blood parasites classification in microscopy images. ISBI 2024: 1-5 - 2023
- [c7]Daniel Capellán-Martín, Juan J. Gomez-Valverde, David Bermejo-Peláez, María J. Ledesma-Carbayo:
A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection. ISBI 2023: 1-5 - [c6]Daniel Capellán-Martín, Juan J. Gómez-Valverde, Ramon Sánchez-Jacob, David Bermejo-Peláez, Lara García-Delgado, Elisa López-Varela, María J. Ledesma-Carbayo:
Deep learning-based lung segmentation and automatic regional template in chest x-ray images for pediatric tuberculosis. Medical Imaging: Computer-Aided Diagnosis 2023 - [i2]Daniel Capellán-Martín, Juan J. Gomez-Valverde, Ramon Sánchez-Jacob, David Bermejo-Peláez, Lara García-Delgado, Elisa López-Varela, María J. Ledesma-Carbayo:
Deep learning-based lung segmentation and automatic regional template in chest X-ray images for pediatric tuberculosis. CoRR abs/2301.13786 (2023) - [i1]Daniel Capellán-Martín, Juan J. Gómez-Valverde, David Bermejo-Peláez, María J. Ledesma-Carbayo:
A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection. CoRR abs/2309.02140 (2023) - 2022
- [c5]David Bermejo-Peláez, Raúl San José Estépar, M. Fernández-Velilla, Carmelo Palacios Miras, Guillermo Gallardo Madueño, M. Benegas, Miguel A. Luengo-Oroz, J. Sellarés, M. Sánchez, Gorka Bastarrika, German R. Peces-Barba, Luis Miguel Seijo Maceiras, María J. Ledesma-Carbayo:
Deep-learning characterization and quantification of COVID-19 pneumonia lesions from chest CT images. Medical Imaging: Computer-Aided Diagnosis 2022 - 2021
- [c4]Lin Lin, David Bermejo-Peláez, Daniel Capellán-Martín, Daniel Cuadrado, Cristina Rodríguez, Lydia García, Nuria Díez, Rocío Tomé, María Postigo, María-Jesus Ledesma-Carbayo, Miguel A. Luengo-Oroz:
Combining collective and artificial intelligence for global health diseases diagnosis using crowdsourced annotated medical images. EMBC 2021: 3344-3348
2010 – 2019
- 2019
- [j2]Daniel Jimenez-Carretero, David Bermejo-Peláez, Pietro Nardelli, Patricia Fraga, Eduardo Fraile Moreno, Raúl San José Estépar, María J. Ledesma-Carbayo:
A graph-cut approach for pulmonary artery-vein segmentation in noncontrast CT images. Medical Image Anal. 52: 144-159 (2019) - [c3]David Bermejo-Peláez, Yuka Okajima, George R. Washko, María-Jesus Ledesma-Carbayo, Raúl San José Estépar:
A SR-NET 3D-to-2D Architecture For Paraseptal Emphysema Segmentation. ISBI 2019: 303-306 - 2018
- [j1]Pietro Nardelli, Daniel Jimenez-Carretero, David Bermejo-Peláez, George R. Washko, Farbod N. Rahaghi, María J. Ledesma-Carbayo, Raúl San José Estépar:
Pulmonary Artery-Vein Classification in CT Images Using Deep Learning. IEEE Trans. Medical Imaging 37(11): 2428-2440 (2018) - [c2]David Bermejo-Peláez, Raúl San José Estépar, María J. Ledesma-Carbayo:
Emphysema classification using a multi-view convolutional network. ISBI 2018: 519-522 - 2017
- [c1]Pietro Nardelli, Daniel Jimenez-Carretero, David Bermejo-Peláez, María J. Ledesma-Carbayo, Farbod N. Rahaghi, Raúl San José Estépar:
Deep-learning strategy for pulmonary artery-vein classification of non-contrast CT images. ISBI 2017: 384-387
Coauthor Index
aka: María-Jesus Ledesma-Carbayo
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