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Ferran C, Giró-i-Nieto X, Marqués F, Casas JR. BPT Enhancement based on Syntactic and Semantic criteria. In Semantic Multimedia. Berlin / Heidelberg: Springer; 2006. pp. 184–198.
Cumplido-Mayoral I. Biological brain-age prediction using Machine Learning on neuroimaging data: Links with pathophysiological mechanisms, dementia risk factors and cognitive decline. Vilaplana V, Gispert JD. Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra. 2024.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration. In Alzheimer's Association International Conference. 2022.
Cumplido-Mayoral I, Mila-Aloma M, Lorenzini L, Wink AMeije, Mutsaerts H, Haller S, et al.. Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex. In 15th Clinical Trials on Alzheimer’s Disease Conference (CTAD). San Francisco, USA; 2022.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration stratified by sex. eLife. 2023;12.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration. In Alzheimer's Association International Conference. 2022.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration. In Alzheimer's Association International Conference. 2022.
Cumplido-Mayoral I, Mila-Aloma M, Lorenzini L, Wink AMeije, Mutsaerts H, Haller S, et al.. Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex. In 15th Clinical Trials on Alzheimer’s Disease Conference (CTAD). San Francisco, USA; 2022.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration stratified by sex. eLife. 2023;12.
Ferran C, Casas JR. Binary-Partition Tree creation using a quasi-inclusion criterion. In 8th International Conference on Information Visualization (IV04). 2004. pp. 259–264.  (217.17 KB)
Wang L, Nie D, Li G, Puybareau E, Dolz J, Zhang Q, et al.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge. IEEE Transactions on Medical Imaging. 2019;.
Wang L, Nie D, Li G, Puybareau E, Dolz J, Zhang Q, et al.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge. IEEE Transactions on Medical Imaging. 2019;.
Hernandez C, Combalia M, Podlipnik S, Codella NCF, Rotemberg V, Halpern AC, et al.. Bcn20000: Dermoscopic lesions in the wild. Nature - Scientific Data. 2024;11.
Combalia M, Codella NCF, Rotemberg V, Helba B, Vilaplana V, Reiter O, et al.. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
Hernandez C, Combalia M, Podlipnik S, Codella NCF, Rotemberg V, Halpern AC, et al.. Bcn20000: Dermoscopic lesions in the wild. Nature - Scientific Data. 2024;11.
Combalia M, Codella NCF, Rotemberg V, Helba B, Vilaplana V, Reiter O, et al.. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
Combalia M, Codella NCF, Rotemberg V, Helba B, Vilaplana V, Reiter O, et al.. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
Hernandez C, Combalia M, Podlipnik S, Codella NCF, Rotemberg V, Halpern AC, et al.. Bcn20000: Dermoscopic lesions in the wild. Nature - Scientific Data. 2024;11.
Correa P, Czyz J, Marqués F, Umeda T, Marichal X, Macq B. Bayesian approach for morphology based 2D human motion capture. IEEE transactions on multimedia. 2007;9:754–765.
Correa P, Czyz J, Marqués F, Umeda T, Marichal X, Macq B. Bayesian approach for morphology based 2D human motion capture. IEEE transactions on multimedia. 2007;9:754–765.
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Caros M, Garolera M, Radeva P, Giró-i-Nieto X. Automatic Reminiscence Therapy for Dementia. In ACM International Conference on Multimedia Retrieval (ICMR). Dublin, Ireland: ACM; 2020.  (4.37 MB)
Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Augmented V-Net for White Matter Hyperintensities segmentation. In WMH Segmentation Challenge, Brain-lesion Workshop, MICCAI 2017 . 2017.
Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Augmented V-Net for White Matter Hyperintensities segmentation. In WMH Segmentation Challenge, Brain-lesion Workshop, MICCAI 2017 . 2017.
Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Augmented V-Net for infant brain segmentation. In MICCAI Grand Challenge on 6-month Infant Brain MRI Segmentation, MICCAI 2017. 2017.
Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Augmented V-Net for infant brain segmentation. In MICCAI Grand Challenge on 6-month Infant Brain MRI Segmentation, MICCAI 2017. 2017.

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