J
Jordina Torrents-Barrena
Researcher at Rovira i Virgili University
Publications - 31
Citations - 435
Jordina Torrents-Barrena is an academic researcher from Rovira i Virgili University. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 8, co-authored 23 publications receiving 236 citations.
Papers
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Journal ArticleDOI
Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network
Vivek Kumar Singh,Hatem A. Rashwan,Santiago Romani,Farhan Akram,Nidhi Pandey,Md. Mostafa Kamal Sarker,Adel Saleh,Meritexell Arenas,Miguel Arquez,Domenec Puig,Jordina Torrents-Barrena +10 more
TL;DR: In this paper, a conditional Generative Adversarial Network (cGAN) was proposed to segment a breast tumor within a region of interest (ROI) in a mammogram.
Posted Content
Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural Network
Vivek Kumar Singh,Hatem A. Rashwan,Santiago Romani,Farhan Akram,Nidhi Pandey,Md. Mostafa Kamal Sarker,Adel Saleh,Meritexell Arenas,Miguel Arquez,Domenec Puig,Jordina Torrents-Barrena +10 more
TL;DR: A conditional Generative Adversarial Network (cGAN) devised to segment a breast mass within a region of interest (ROI) in a mammogram outperforms several state-of-the-art approaches.
Book ChapterDOI
Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification
Vivek Kumar Singh,Santiago Romani,Hatem A. Rashwan,Farhan Akram,Nidhi Pandey,Md. Mostafa Kamal Sarker,Saddam Abdulwahab,Jordina Torrents-Barrena,Adel Saleh,Miguel Arquez,Meritxell Arenas,Domenec Puig +11 more
TL;DR: It is hypothesized that the cGAN structure is well-suited to accurately outline the mass area, especially when the training data is limited, and experiments performed confirm this hypothesis with very high Dice coefficient and Jaccard index outperforming the scores obtained by other state-of-the-art approaches.
Journal ArticleDOI
Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images
TL;DR: A bank of Gabor filters to calculate the mean, standard deviation, skewness and kurtosis features by four-sized evaluation windows is proposed and both confusion matrix and accuracy are calculated to assess the results of the proposed algorithm.
Proceedings ArticleDOI
Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images
Saul Calderon-Ramirez,R. Giri,Shengxiang Yang,Armaghan Moemeni,Mario Umana,David Elizondo,Jordina Torrents-Barrena,Miguel A. Molina-Cabello +7 more
TL;DR: A semi-supervised deep learning framework based on the Mix Match architecture to classify chest X-rays into Covid-19, pneumonia and healthy cases is developed and test and shows an accuracy increase of around 15% under low labelled / unlabelled data ratio.