The submitted work presents MEDPSeg, a computed tomography lung segmentation and quantification tool, a software wrapping around Diedre’s PhD work. Go give it a try at https://github.com/MICLab-Unicamp/medpseg. We have an online demo!

Checkout the paper [1] at this link

[1] Diedre S. Carmo, Jean A. Ribeiro, Alejandro P. Comellas, Joseph M. Reinhardt, Sarah E. Gerard, Letícia Rittner, Roberto A. Lotufo, “MEDPSeg: an offline pulmonary segmentation and quantification tool for ground‑glass opacities, consolidation, and other pulmonary structures on computed tomography,” Proc. SPIE 13926, Medical Imaging 2026: Computer-Aided Diagnosis, 139260A (2 April 2026); https://doi.org/10.1117/12.3087511

Representing our lab, Diedre Carmo and Letícia Lopes presented our research on deep learning models for chest X-ray classification, focusing on deployment optimization and fairness evaluation in healthcare applications.

Accepted papers:

• “Avaliação da quantização de modelos visuais de linguagem para implantação em ambiente hospitalar” — Rafael Dosso, Diedre Carmo, and Letícia Rittner.
• “Framework para avaliação de fairness em modelos de classificação aplicados à saúde” — Letícia Lopes, Diedre Carmo, and Letícia Rittner.

And the cherry on top  — Leticia Lopes earned an Honorable Mention for Best Student Paper!

Our group had three papers accepted and presented at the 2024 edition of the International Symposium on Medical Information Processing and Analysis (SIPAIM), in Antigua, Guatemala:

• “Assessing MedSAM’s Generalization to White Matter Hyperintensities in Magnetic Resonance Imaging”. Joany Rodrigues, Diedre Santos, and Leticia Rittner.
• “Enhancing fMRS Data Quality and GABA Quantification Using SpectroViT: A Deep Learning Reconstruction Approach”. Wesna Araujo, Ricardo Landim, Thiago Costa, Elvis Silva, Gabriela Castellano and Leticia Rittner.
• “Training a ViT model on shape signatures for quality control of MRI corpus callosum segmentations”. Suellen Silva and Leticia Rittner.

Our lab students, Diedre Carmo and Wesna Araujo, had the opportunity to attend the conference and present their work.

• “FOD-Swin-Net: angular super resolution of fiber orientation distribution using a transformer-based deep model” – by Mateus Oliveira
• “Classification of pulmonary embolism on computed tomography angiography using artificial intelligence” – by Beatriz Celante

Members of our lab will be travelling to Athens (Greece) to present our work.

Our solution, based on a Vision Transformer, was able to reconstruct an hyperspectral image with 61 channels from a simple RGB + NIR image (4 channels). The research was partially funded by the Instituto de Pesquisas Eldorado.

Members of our lab will be traveling to the conference to present our work.

• “Magnetic Resonance Spectroscopy Fitting through Spectrogram and Vision Transformers”. Marcio Almeida, Gabriel Dias, Mateus Oliveira and Leticia Rittner
• “DTI-based Corpus Callosum parcellation using the Tensorial Morphological Gradient and Self-Organizing Maps”. Caio Santana, Thays Santos, Joany Rodrigues, Paulo Julio, Simone Appenzeller and Leticia Rittner

Members of our lab traveled to these conferences to present our work.