Adrià Casamitjana

Biography

I recieved the degree in Electrical Engineering in 2015 from the Universitat Politècnica de Catalunya (UPC) and M.Sc in Wireless Systems in 2015, from Kungliga Tekniska Högskolan (KTH). I am currently enrolled in a Ph.D program in the Image Processing Group at UPC (GPI), holding a scholarship of the Spanish Government. My main research area is focused on biomedical aplications, with great interest in machine learning and statistics.

I am involved in a project collaboration between the GPI and Fundació Pasqual Maragall (FPM), working on Alzheimer Disease.

Journal Articles top

In Press
A. Casamitjana, Petrone, P., Molinuevo, J. Luis, Gispert, J. D., and Vilaplana, V., “Projection to Latent Spaces disentangles pathological effects on brain morphology in the asymptomatic phase of Alzheimer’s disease”, Frontiers in Neurology, section Applied Neuroimaging, In Press. Google Scholar BibTex

2020
A. Casamitjana, Vilaplana, V., Puch, S., Aduriz, A., Lopez, C., Operto, G., Cacciaglia, R., Falcon, C., Molinuevo, J. L., and Gispert, J. D., “NeAT: a nonlinear analysis toolbox for neuroimaging”, Neuroinformatics, 2020. DOI Google Scholar BibTex

2019
L. Wang, Nie, D., Li, G., Puybareau, E., Dolz, J., Zhang, Q., Wang, F., Xia, J., Wu, Z., Chen, J., -HanThung, K., Bui, T. Duc, Shin, J., Zeng, G., Zheng, G., Fonov, V. S., Doyle, A., Xu, Y., Moeskops, P., Pluim, J., Desrosiers, C., Ben Ayed, I., Sanroma, G., Benkarim, O., Casamitjana, A., Vilaplana, V., Lin, W., Li, G., and Shen, D., “Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge”, IEEE Transactions on Medical Imaging, 2019. DOI Google Scholar BibTex
H. Kuijf, Biesbroek, M., de Bresser, J., Heinen, R., Andermatt, S., Bento, M., Berseth, M., Belyaev, M., Cardoso, J., Casamitjana, A., Collins, L., Dadar, M., Georgiou, A., Ghafoorian, M., Jin, D., Khademi, A., Knight, J., Li, H., Llado, X., Luna, M., Mahmood, Q., McKinley, R., Mehrtash, A., Ourselin, S., Park, B. -yong, Park, H., Park, S. Hyun, Pezold, S., Puybareau, E., Rittner, L., Sudre, C., Valverde, S., Vilaplana, V., Wiest, R., Xu, Y., Xu, Z., Zeng, G., Zhang, J., Zheng, G., Chen, C., van der Flier, W., Barkhof, F., Viergever, M., and Biessels, G. Jan, “Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge”, IEEE Transactions on Medical Imaging, 2019. DOI Google Scholar BibTex
P. Petrone, Casamitjana, A., Falcon, C., Cànaves, M. Artigues, Operto, G., Cacciaglia, R., Molinuevo, J. Luis, Vilaplana, V., and Gispert, J. D., “Prediction of amyloid pathology in cognitively unimpaired individuals using voxelwise analysis of longitudinal structural brain MRI”, Alzheimer's Research & Therapy, vol. 11, no. 1, 2019. DOI Google Scholar BibTex

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Book Chapters and Books top

2018
A. Casamitjana, Catà, M., Sánchez, I., Combalia, M., and Vilaplana, V., “Cascaded V-Net Using ROI Masks for Brain Tumor Segmentation”, in Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017, Crimi A., Bakas S., Kuijf H., Menze B., Reyes M. (eds)., vol. 10670, Cham: Springer, 2018, pp. 381-391. DOI Google Scholar BibTex
A. Casamitjana, Vilaplana, V., Petrone, P., Molinuevo, J. Luis, and Gispert, J. D., “Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer’s Disease”, in PRedictive Intelligence in MEdicine, vol. 11121, Springer International Publishing, 2018, pp. 60-67. DOI Google Scholar BibTex

2017
A. Casamitjana, Puch, S., Aduriz, A., and Vilaplana, V., “3D Convolutional Neural Networks for Brain Tumor Segmentation: a comparison of multi-resolution architectures”, in Lecture Notes in Computer Vision, vol. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Springer, 2017, pp. 150-161. Google Scholar BibTex

Conference Papers top

2019
A. Casamitjana, Petrone, P., Falcon, C., Artigues, M., Operto, G., Cacciaglia, R., Molinuevo, J. L., Vilaplana, V., and Gispert, J. D., “Detection of Amyloid Positive Cognitively unimpaired individuals using voxel-based machine learning on structural longitudinal brain MRI”, in Alzheimer's Association International Conference, 2019. Google Scholar BibTex

2018
P. Petrone, Casamitjana, A., Falcon, C., Artigues, M., Operto, G., Skouras, S., Cacciaglia, R., Molinuevo, J. L., Vilaplana, V., and Gispert, J. D., “Characteristic Brain Volumetric Changes in the AD Preclinical Signature”, in Alzheimer's Association International Conference, Chicago, USA, 2018. Google Scholar BibTex
A. Casamitjana, Petrone, P., Artigues, M., Molinuevo, J. L., Gispert, J. D., and Vilaplana, V., “Projection to Latent Spaces Disentangles Specific Cerebral Morphometric Patterns Associated to Aging and Preclinical AD”, in Alzheimer's Association International Conference, Chicago, USA, 2018. Google Scholar BibTex
A. Casamitjana, Vilaplana, V., Petrone, P., Molinuevo, J. Luis, and Gispert, J. D., “Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease”, in Workshop on Predictive Intelligence in Medicine (PRIME), MICCAI, Granada, Spain, 2018. Google Scholar BibTex
S. Bakas, Reyes, M., Jakab, A., Bauer, S., Casamitjana, A., Vilaplana, V., and Al., et., “Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge”, in MICCAI - Multimodal Brain Tumor Segmentation Challenge, 2018. Google Scholar BibTex

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Theses top

2019
A. Casamitjana, “Study of early stages of Alzheimer’s disease using magnetic resonance imaging”, Universitat Politècnica de Catalunya, Barcelona, 2019. Google Scholar BibTex

Other top

2018
C. Bonín Roselló, “Brain lesion segmentation using Convolutional Neuronal Networks”. 2018. Google Scholar BibTex (3.15 MB)	Ms Thesis

2017
D. Rodríguez Castelló, “Extracción de cráneo en imágenes de resonancia magnética del cerebro utilizando una red neuronal convolucional 3D”. 2017. Google Scholar BibTex	Ms Thesis

2016
M. Catà, “Feature Selection Methods for Predicting Pre-Clinical Stage in Alzheimer's Disease”. 2016. Google Scholar BibTex (4.52 MB)	Ms Thesis

Projects top

	MALEGRA - Multimodal Signal Processing and Machine Learning on Graphs	National	Jan 2017	Jun 2021
	BigGraph - Heterogeneous information and graph signal processing for the Big Data era. Application to high-throughput, remote sensing, multimedia and human computer interfaces.	National	Jan 2014	Dec 2017