MICLab-NeuralMind consortium wins MICCAI competition
Our solution using AI to diagnose COVID-19 using computed tomography and chest x-rays received the COVID Solution Award at the 23rd International conference of MICCAI (Medical Image Computing & Computer Assisted Intervention) 2020. The winners were announced by MICCAI, NVIDIA Inception, and SIPAIM, in the MICCAI Startups Village pitch competition. The event celebrated the achievements of innovative startups improving information processing, machine learning, and computational modeling in medical image computing and computer assisted interventions. S...Continue Reading
MICLab-Neuralmind consortium working on COVID19 detection
MICLab and Neuralmind collaborated closely in order to develop a solution for COVID19 detection. The consortium presented an efficient solution to the ideiaGov challenge: COVID19 Diagnosis through computed tomography and chest X-ray images. Know more about this challenge here .Continue Reading
Opportunity: Postdoctoral Fellowship
We are looking for talented candidates with innovative ideas to develop, implement, disseminate and evaluate machine learning (ML) techniques in the analysis of medical images and image-related data. The position is part of the Project “Computational tools for the diagnosis, detection and prognosis of COVID-19: analysis and development of methods using deep convolutional networks with computed tomography data”. The research will be developed at the Medical Image Computing Lab (MICLab), University of Campinas (
Paper published at Journal of Neuroscience Methods
Check our last publication A framework for quality control of corpus callosum segmentation in large-scale studies at Journal of Neuroscience Methods. In this work we proposed a framework for automatic quality control of corpus callosum segmentations based on a machine learning SVM technique.Continue Reading
Poster Presentation at MICCAI CDMRI 19 - Shenzhen, China
MICCAI 2019 INTERNATIONAL WORKSHOP ON COMPUTATIONAL DIFFUSION MRI (CDMRI - Shenzhen, China) is a workshop focused on diffusion MRI that brings the most important researchers and young researchers together.
This workshop is composed of papers and poster presentations, experts´ lectures, and challenges.
Our group presented a poster entitled "CONVOLUTIONAL NEURAL NETWORK ON DTI DATA FOR SUB-CORTICAL BRAIN STRUCTURE SEGMENTATION" that its paper is going to be published at MICCAI Proceedings.Continue Reading
Medical Image Quality Workshop
The workshop will take place at FEEC/Unicamp, on October, 25th, November 1st and 11th.
Lectures and challenge about medical images acquisition and quality control!!
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Paper Acccepted on the MICCAI CDMRI 19
Our researchers had a paper accepted to the CDMRI 2019 International Conference. The event will be in Shenzhen, China 13-17 October 2019.
"Convolutional Neural Network on DTI data for Sub-cortical Brain Structure Segmentation". Gustavo Retuci Pinheiro, Diedre Carmo, Clarissa Yasuda, and Leticia Rittner.Continue Reading
participation on 2019 SCHOOL ON BRAIN CONNECTOMICS
Two of our researchers are participating in the 2019 SCHOOL ON BRAIN CONNECTOMICS.
This School is happening in University of Verona - Italy, September 23 - 27.
In this event, supported by MICCAI and IEEE Signal Processing Society, some of the main authors of brain imaging and connectomics were presenting their work and giving lectures and workshops.Continue Reading
Poster Presentation in the International Conference on Medical Imaging with Deep Learning
The MIDL conference aims to be a forum for deep learning researchers, clinicians and health-care companies to take a leap in the application of deep learning based automatic image analysis in disease screening, diagnosis, prognosis, treatment selection and treatment monitoring. In its 2019 edition in London, our research group participated in the conference with an Extended Abstract presented as a poster presentation, Extended 2D Consensus Hippocampus Segmentation.Continue Reading
Best Paper Award Master degree student - 6th BRAINN Congress
The paper “A Brazilian dataset domain adaptation to diagnose Alzheimer’s disease and subjects with cognitive deficit using convolutional neural networks“ won the award for the best paper in the Master degree category at the 6th edition of the BRAINN Congress. Authors: Mariana Pereira (UNICAMP); Thamires Magalhães (UNICAMP); Roberto Lotufo (UNICAMP); Márcio Balthazar (Unicamp) e Leticia Rittner (UNICAMP). The work will be published at Journal of Epilepsy and Clinical Neurophysiology, 2019.Continue Reading