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About

João Pedrosa was born in Figueira da Foz, Portugal, in 1990. He received the M.Sc. degree in biomedical engineering from the University of Porto, Porto, Portugal, in 2013 and the Ph.D. degree in biomedical sciences with KU Leuven, Leuven, Belgium, in 2018. He is currently a postdoctoral researcher at INESC TEC, Porto Portugal working on image processing and computer-aided diagnosis in lung cancer CT screening and diabetic retinopathy. His research interests include medical imaging acquisition and processing, machine learning and applied research for improved patient care.

Interest
Topics
Details

Details

004
Publications

2021

LNDb Challenge on automatic lung cancer patient management

Authors
Pedrosa, J; Aresta, G; Ferreira, C; Atwal, G; Phoulady, HA; Chen, X; Chen, R; Li, J; Wang, L; Galdran, A; Bouchachia, H; Kaluva, KC; Vaidhya, K; Chunduru, A; Tarai, S; Nadimpalli, SPP; Vaidya, S; Kim, I; Rassadin, A; Tian, Z; Sun, Z; Jia, Y; Men, X; Ramos, I; Cunha, A; Campilho, A;

Publication
Medical Image Analysis

Abstract

2020

Interplay of cardiac remodelling and myocardial stiffness in hypertensive heart disease: a shear wave imaging study using high-frame rate echocardiography

Authors
Cvijic, M; Bézy, S; Petrescu, A; Santos, P; Orlowska, M; Chakraborty, B; Duchenne, J; Pedrosa, J; Vanassche, T; D'Hooge, J; Voigt, JU;

Publication
European Heart Journal - Cardiovascular Imaging

Abstract
Abstract Aims To determine myocardial stiffness by means of measuring the velocity of naturally occurring myocardial shear waves (SWs) at mitral valve closure (MVC) and investigate their changes with myocardial remodelling in patients with hypertensive heart disease. Methods and results Thirty-three treated arterial hypertension (HT) patients with hypertrophic left ventricular (LV) remodelling (59?±?14?years, 55% male) and 26 aged matched healthy controls (55±15?years, 77% male) were included. HT patients were further divided into a concentric remodelling (HT1) group (13 patients) and a concentric hypertrophy (HT2) group (20 patients). LV parasternal long-axis views were acquired with an experimental ultrasound scanner at 1266?±?317 frames per seconds. The SW velocity induced by MVC was measured from myocardial acceleration maps. SW velocities differed significantly between HT patients and controls (5.83?±?1.20 m/s vs. 4.04?±?0.96 m/s; P?<?0.001). In addition, the HT2 group had the highest SW velocities (P?<?0.001), whereas values between controls and the HT1 group were comparable (P?=?0.075). Significant positive correlations were found between SW velocity and LV remodelling (interventricular septum thickness: r?=?0.786, P?<?0.001; LV mass index: r?=?0.761, P?<?0.001). SW velocity normalized for wall stress indicated that myocardial stiffness in the HT2 group was twice as high as in controls (P?<?0.001), whereas values of the HT1 group overlapped with the controls (P?=?1.00). Conclusions SW velocity as measure of myocardial stiffness is higher in HT patients compared with healthy controls, particularly in advanced hypertensive heart disease. Patients with concentric remodelling have still normal myocardial properties whereas patients with concentric hypertrophy show significant stiffening.

2020

Automatic Lung Reference Model

Authors
Machado, M; Ferreira, CA; Pedrosa, J; Negrao, E; Rebelo, J; Leitao, P; Carvalho, AS; Rodrigues, MC; Ramos, I; Cunha, A; Campilho, A;

Publication
IFMBE Proceedings - XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019

Abstract

2020

Automatic lung nodule detection combined with gaze information improves radiologists' screening performance

Authors
Aresta, G; Ferreira, C; Pedrosa, J; Araujo, T; Rebelo, J; Negrao, E; Morgado, M; Alves, F; Cunha, A; Ramos, I; Campilho, A;

Publication
IEEE Journal of Biomedical and Health Informatics

Abstract

2020

LNDetector: A Flexible Gaze Characterisation Collaborative Platform for Pulmonary Nodule Screening

Authors
Pedrosa, J; Aresta, G; Rebelo, J; Negrao, E; Ramos, I; Cunha, A; Campilho, A;

Publication
IFMBE Proceedings

Abstract
Lung cancer is the deadliest type of cancer worldwide and late detection is one of the major factors for the low survival rate of patients. Low dose computed tomography has been suggested as a potential early screening tool but manual screening is costly, time-consuming and prone to interobserver variability. This has fueled the development of automatic methods for the detection, segmentation and characterisation of pulmonary nodules but its application to the clinical routine is challenging. In this study, a platform for the development, deployment and testing of pulmonary nodule computer-aided strategies is presented: LNDetector. LNDetector integrates image exploration and nodule annotation tools as well as advanced nodule detection, segmentation and classification methods and gaze characterisation. Different processing modules can easily be implemented or replaced to test their efficiency in clinical environments and the use of gaze analysis allows for the development of collaborative strategies. The potential use of this platform is shown through a combination of visual search, gaze characterisation and automatic nodule detection tools for an efficient and collaborative computer-aided strategy for pulmonary nodule screening. © 2020, Springer Nature Switzerland AG.

Supervised
thesis

2020

Generative Adversarial Networks in Automated Chest Radiography Screening

Author
Martim Quintas e Sousa

Institution
UP-FEUP