Adrià Casamitjana

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PhD Candidate | adria.casamitjana@upc.edu |
Office | Phone |
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D5-119 | +34 934 011 627 |
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
“NeAT: a nonlinear analysis toolbox for neuroimaging”, Neuroinformatics, 2020. | ,
“Projection to Latent Spaces disentangles pathological effects on brain morphology in the asymptomatic phase of Alzheimer’s disease”, Frontiers in Neurology, section Applied Neuroimaging, vol. 11, 2020. | ,
“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. | ,
“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. | ,
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
“Detection of Amyloid Positive Cognitively unimpaired individuals using voxel-based machine learning on structural longitudinal brain MRI”, in Alzheimer's Association International Conference, 2019. | ,
“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. | ,
Theses top
“Study of early stages of Alzheimer’s disease using magnetic resonance imaging”, Universitat Politècnica de Catalunya, Barcelona, 2019. | ,
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
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SGR17 - Image and Video Processing Group | National | Jan 2017 | Sep 2021 |
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MALEGRA - Multimodal Signal Processing and Machine Learning on Graphs | National | Jan 2017 | Jun 2021 |
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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 |
Research Areas top
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Biomedical Applications | Internal | Jan 2012 | Dec 2024 |
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Preclinical Alzheimer's Disease | Internal | Jan 2015 | Dec 2024 |
Demos and Resources top
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VNeAT (Voxel-wise Neuroimaging Analysis Toolbox) | Software | Jun 2017 |