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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, XY; Chen, RZ; Li, JL; Wang, LS; Galdran, A; Bouchachia, H; Kaluva, KC; Vaidhya, K; Chunduru, A; Tarai, S; Nadimpalli, SPP; Vaidya, S; Kim, I; Rassadin, A; Tian, ZH; Sun, ZW; Jia, YZ; Men, XJ; Ramos, I; Cunha, A; Campilho, A;

Publication
Medical Image Analysis

Abstract

2021

Extracting neuronal activity signals from microscopy recordings of contractile tissue using B-spline Explicit Active Surfaces (BEAS) cell tracking

Authors
Kazwiny, Y; Pedrosa, J; Zhang, ZQ; Boesmans, W; D'hooge, J; Vanden Berghe, P;

Publication
SCIENTIFIC REPORTS

Abstract
Ca2+ imaging is a widely used microscopy technique to simultaneously study cellular activity in multiple cells. The desired information consists of cell-specific time series of pixel intensity values, in which the fluorescence intensity represents cellular activity. For static scenes, cellular signal extraction is straightforward, however multiple analysis challenges are present in recordings of contractile tissues, like those of the enteric nervous system (ENS). This layer of critical neurons, embedded within the muscle layers of the gut wall, shows optical overlap between neighboring neurons, intensity changes due to cell activity, and constant movement. These challenges reduce the applicability of classical segmentation techniques and traditional stack alignment and regions-of-interest (ROIs) selection workflows. Therefore, a signal extraction method capable of dealing with moving cells and is insensitive to large intensity changes in consecutive frames is needed. Here we propose a b-spline active contour method to delineate and track neuronal cell bodies based on local and global energy terms. We develop both a single as well as a double-contour approach. The latter takes advantage of the appearance of GCaMP expressing cells, and tracks the nucleus' boundaries together with the cytoplasmic contour, providing a stable delineation of neighboring, overlapping cells despite movement and intensity changes. The tracked contours can also serve as landmarks to relocate additional and manually-selected ROIs. This improves the total yield of efficacious cell tracking and allows signal extraction from other cell compartments like neuronal processes. Compared to manual delineation and other segmentation methods, the proposed method can track cells during large tissue deformations and high-intensity changes such as during neuronal firing events, while preserving the shape of the extracted Ca2+ signal. The analysis package represents a significant improvement to available Ca2+ imaging analysis workflows for ENS recordings and other systems where movement challenges traditional Ca2+ signal extraction workflows.

2021

A multi-task CNN approach for lung nodule malignancy classification and characterization

Authors
Marques, S; Schiavo, F; Ferreira, CA; Pedrosa, J; Cunha, A; Campilho, A;

Publication
Expert Systems with Applications

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

Supervised
thesis

2020

Generative Adversarial Networks in Automated Chest Radiography Screening

Author
Martim Quintas e Sousa

Institution
UP-FEUP