activity
20142026
most citedA novel approach for the automated segmentation and volume quantification of cardiac fats on computed tomography

78 citations · 359 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

FU-Mamba: A Frequency-Enhanced Dynamic Scanning Framework for Oralscan Image Segmentation

Xinxin Zhao, Jinpeng Ye, Bo Wei +8

Oralscan image segmentation is essential for computer-aided diagnosis and treatment planning in digital dentistry. However, existing visual state space models (SSMs) often rely on…

cs.CV2026

Mathematical Morphology in Machine Learning

Erick Oliveira Rodrigues, Aura Conci

This work introduces mathematical morphology-an established visual computing theory-into machine learning to exploit shape and density aspects often overlooked by standard techniqu…

cs.CV2026★ 12 cited

An Approach for Thyroid Nodule Analysis Using Thermographic Images

J. R. González, É. O. Rodrigues, C. P. Damião +6

Thyroid cancer is said to be the second most common type of cancer in female individuals and the third in males by 2030, according to projections. In general, detecting cancer in i…

cs.CV2026★ 73 cited

ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach

Erick O. Rodrigues, Aura Conci, Panos Liatsis

Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy…

cs.CV2026★ 10 cited

A simple approach for biometrics: Finger-knuckle prints recognition based on a Sobel filter and similarity measures

E. O. Rodrigues, T. M. Porcino, Aura Conci +1

The objective of this work is to propose a novel methodology for the finger knuckle print recognition, which is essentially a digital photo of the finger-knuckle region. We have em…

cs.CV2022★ 43 cited

Machine learning in the prediction of cardiac epicardial and mediastinal fat volumes

É. O. Rodrigues, V. H. A. Pinheiro, P. Liatsis +1

We propose a methodology to predict the cardiac epicardial and mediastinal fat volumes in computed tomography images using regression algorithms. The obtained results indicate that…