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
“Prediction of amyloid pathology in cognitively unimpaired individuals using voxelwise analysis of longitudinal structural brain MRI”, Alzheimer's Research & Therapy, In Press. | ,
“Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease: a predictive study”, IEEE Journal of Biomedical and Health Informatics, In Press. | ,
“Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge”, IEEE Transactions on Medical Imaging, 2019. | ,
“Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge”, IEEE Transactions on Medical Imaging, 2019. | ,
“MRI-Based Screening of Preclinical Alzheimer's Disease for Prevention Clinical Trials”, Journal of Alzheimer's Disease, vol. 64, no. 4, 2018. | ,
Book Chapters and Books top
“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. | ,
“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. | ,
“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. | ,
Conference Papers top
“Characteristic Brain Volumetric Changes in the AD Preclinical Signature”, in Alzheimer's Association International Conference, Chicago, USA, 2018. | ,
“Projection to Latent Spaces Disentangles Specific Cerebral Morphometric Patterns Associated to Aging and Preclinical AD”, in Alzheimer's Association International Conference, Chicago, USA, 2018. | ,
“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. | ,
“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. | ,
“Magnetic Resonance Imaging as a valuable tool for Alzheimer's disease screening”, in Alzheimer’s Association International Conference, London, 2017, 2017. | ,
Other top
“Brain lesion segmentation using Convolutional Neuronal Networks”. 2018.![]() |
, Ms Thesis |
“Extracción de cráneo en imágenes de resonancia magnética del cerebro utilizando una red neuronal convolucional 3D”. 2017. | ,Ms Thesis |
“Feature Selection Methods for Predicting Pre-Clinical Stage in Alzheimer's Disease”. 2016.![]() |
, Ms Thesis |
Projects top
Research Areas top
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Preclinical Alzheimer's Disease | Internal | Jan 2015 | Dec 2021 |
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Biomedical Applications | Internal | Jan 2012 | Dec 2020 |
Demos and Resources top
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VNeAT (Voxel-wise Neuroimaging Analysis Toolbox) | Software | Jun 2017 |