- I am a post-doc in Center for Medical Image Computing (CMIC) at University College of London, working with Dr. Juan Eugenio Iglesias in developing next generation tools for neuroimage analysis.
[Curriculum Vitae], [Google Scholar]
- My main research intests include brain MRI segmentation, statistical learning for multimodal data and bayesian modeling. Over the course of my PhD I have been developing modeling tools to study Alzheimer’s diesease (AD) using MRI, with special focus in early AD stages and its application to clinical trials.
- I did my PhD on the study of early stages of AD using machine learning and MRI and its application to clinical trials. I worked under the supervision of Dr. Verónica Vilaplana in the Image Processing Group (GPI) at Universitat Politècnica de Catalunya. During my PhD, I collaborated with the BarcelonaBeta Brain Research Centre (BBRC) and I visited the Centre for Medical Image Computing (CMIC) at University College of London working with Dr. Andre Altman.
- October, 2021. Our paper “Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas” has been accepted in Medical Image Analysis.
- Paper: https://arxiv.org/pdf/2104.14873.pdf
- Code: https://github.com/acasamitjana/3dhirest
- Data: https://openneuro.org/datasets/ds003590
- Twitter: https://twitter.com/therelaxationt1/status/1453615376365928449
- October, 2021. Best paper award in SASHIMI, a MICCAI satellite event for our paper “Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images”. Paper: https://arxiv.org/pdf/2107.14449.pdf
- November, 2020. Checkout DeepReg, an open-source learning-based registration framework in tensorflow. Well documented, wildly tested and with demos to get started. Honoured to be part of the core team.
- Code in: https://github.com/DeepRegNet/DeepReg
- October, 2020. MICCAI Conference: coauthor of “3D Reconstruction and Segmentation of Dissection Photographs for MRI-Free Neuropathology” (Tredgigo, et al.) https://arxiv.org/abs/2103.13578
- June 30, 2020. Paper accepted in Scientific Reports: “A multimodal computational pipeline for 3D histology of the human brain” (Mancini et al.)
- June 2, 2020. Paper accepted in Frontiers in Neurology: “Projection to Latent Spaces disentangles pathological effects on brain morphology in the asymptomatic phase of Alzheimer’s disease”. (Casamitjana et al.)
- February, 2020. Paper accepted in Neuroinformatics: “NeAT: a nonlinear analysis toolbox for neuroimaging” (Casamitjana et al.). The code is publicly available through this webpage: https://imatge-upc.github.io/neat-tool/
- July 28, 2019. Paper accepted in IEEE Journal of Biomedical and Helath Informatics (J-BHI): “Shared latent structures between imaging features and biomarkers in early stages of Alzheimer’s disease: a predictive study” (Casamitjana et al.)
- July 23, 2019. Paper accepted in Alzheimer’s Research and Therapy: “Prediction of amyloid pathology in cognitively unimpaired individuals using voxelwise analysis of longitudinal structural brain MRI” (Petrone*, Casamitjana* et al.).
- February 1, 2019. Visiting researcher at CMIC (UCL) under the supervision of Dr. Andre Altman.