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Publicações

Publicações por BIO

2022

Multiple instance learning for lung pathophysiological findings detection using CT scans

Autores
Frade, J; Pereira, T; Morgado, J; Silva, F; Freitas, C; Mendes, J; Negrao, E; de Lima, BF; da Silva, MC; Madureira, AJ; Ramos, I; Costa, JL; Hespanhol, V; Cunha, A; Oliveira, HP;

Publicação
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

Abstract
Lung diseases affect the lives of billions of people worldwide, and 4 million people, each year, die prematurely due to this condition. These pathologies are characterized by specific imagiological findings in CT scans. The traditional Computer-Aided Diagnosis (CAD) approaches have been showing promising results to help clinicians; however, CADs normally consider a small part of the medical image for analysis, excluding possible relevant information for clinical evaluation. Multiple Instance Learning (MIL) approach takes into consideration different small pieces that are relevant for the final classification and creates a comprehensive analysis of pathophysiological changes. This study uses MIL-based approaches to identify the presence of lung pathophysiological findings in CT scans for the characterization of lung disease development. This work was focus on the detection of the following: Fibrosis, Emphysema, Satellite Nodules in Primary Lesion Lobe, Nodules in Contralateral Lung and Ground Glass, being Fibrosis and Emphysema the ones with more outstanding results, reaching an Area Under the Curve (AUC) of 0.89 and 0.72, respectively. Additionally, the MIL-based approach was used for EGFR mutation status prediction - the most relevant oncogene on lung cancer, with an AUC of 0.69. The results showed that this comprehensive approach can be a useful tool for lung pathophysiological characterization.

2022

BIOSIG 2021 Special issue on efficient, reliable, and privacy-friendly biometrics

Autores
Sequeira, AE; Gomez Barrero, M; Damer, N; Correia, PL;

Publicação
IET BIOMETRICS

Abstract

2022

Evaluation of OCA diffusivity in tissues through diffuse reflection spectroscopy

Autores
Martins, IS; Pinheiro, MR; Silva, HF; Tuchin, VV; Oliveira, LM;

Publicação
2022 International Conference Laser Optics, ICLO 2022 - Proceedingss

Abstract
The evaluation of the diffusion properties of optical clearing agents in biological tissues, which are necessary to characterize the transparency mechanisms, has been traditionally made using ex vivo tissues. With the objective of performing such evaluation in vivo, this study was made to evaluate and compare those properties for propylene glycol in skeletal muscle, as obtained with the collimated transmittance and diffuse reflectance kinetics. The diffusion time and the diffusion coefficient of propylene glycol in the muscle that were calculated both from transmittance and reflectance kinetics presented a deviation of 0.8%, a result that opens the possibility to use such a method in vivo. © 2022 IEEE.

2022

Spectroscopic detection of pigments in tissues: correlation with tissue aging and cancer development

Autores
Oliveira, LM; Goncalves, TM; Botelho, AR; Martins, IS; Silva, HF; Carneiro, I; Carvalho, S; Henrique, R; Tuchin, VV;

Publicação
2022 International Conference Laser Optics, ICLO 2022 - Proceedingss

Abstract
The direct calculation of the absorption coefficient spectra of various tissues from spectral measurements allowed to retrieve the contents of melanin and lipofuscin. In the rabbit brain cortex, 1.8 times higher melanin content is explained by the neuron degeneration process. Similar melanin and lipofuscin contents were found in the rabbit pancreas as a result of the tissue aging process. The conversion of 83 % of the melanin in the human normal kidney into lipofuscin in the cancer kidney indicates that lipofuscin can be considered a kidney cancer marker in humans. © 2022 IEEE.

2022

Colon Nuclei Instance Segmentation using a Probabilistic Two-Stage Detector

Autores
Costa, P; Fu, Y; Nunes, J; Campilho, A; Cardoso, JS;

Publicação
CoRR

Abstract

2022

Explainable Biometrics in the Age of Deep Learning

Autores
Neto, PC; Gonçalves, T; Pinto, JR; Silva, W; Sequeira, AF; Ross, A; Cardoso, JS;

Publicação
CoRR

Abstract

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