23 citations · 46 across the 8 of their papers we have counts for
9 papers
Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction
Mohamed El Amine Elforaici, Emmanuel Montagnon, Francisco Perdigon Romero +7
Colorectal liver metastases (CLM) significantly impact colon cancer patients, influencing survival based on systemic chemotherapy response. Traditional methods like tumor grading s…
Multi-Source Domain Adaptation for Object Detection with Prototype-based Mean-teacher
Atif Belal, Akhil Meethal, Francisco Perdigon Romero +2
Adapting visual object detectors to operational target domains is a challenging task, commonly achieved using unsupervised domain adaptation (UDA) methods. Recent studies have show…
Semi-Weakly Supervised Object Detection by Sampling Pseudo Ground-Truth Boxes
Akhil Meethal, Marco Pedersoli, Zhongwen Zhu +2
Semi- and weakly-supervised learning have recently attracted considerable attention in the object detection literature since they can alleviate the cost of annotation needed to suc…
DeepFilter: an ECG baseline wander removal filter using deep learning techniques
Francisco Perdigon Romero, David Castro Piñol, Carlos Román Vázquez Seisdedos
According to the World Health Organization, around 36% of the annual deaths are associated with cardiovascular diseases and 90% of heart attacks are preventable. Electrocardiogram…
Spine intervertebral disc labeling using a fully convolutional redundant counting model
Lucas Rouhier, Francisco Perdigon Romero, Joseph Paul Cohen +1
Labeling intervertebral discs is relevant as it notably enables clinicians to understand the relationship between a patient's symptoms (pain, paralysis) and the exact level of spin…
Predictive Model for Assessment of Pathological Response of Colorectal Liver Metastases to Chemotherapy from CT Images
Francisco Perdigon Romero, Emmanuel Montagnon, Milena Cerny +9
problem with results session, numbers are incorrect, theoretical thinking is no longer valid
End-to-End Discriminative Deep Network for Liver Lesion Classification
Francisco Perdigon Romero, Andre Diler, Gabriel Bisson-Gregoire +5
Colorectal liver metastasis is one of most aggressive liver malignancies. While the definition of lesion type based on CT images determines the diagnosis and therapeutic strategy,…
Multi-Level Batch Normalization In Deep Networks For Invasive Ductal Carcinoma Cell Discrimination In Histopathology Images
Francisco Perdigon Romero, An Tang, Samuel Kadoury
Breast cancer is the most diagnosed cancer and the most predominant cause of death in women worldwide. Imaging techniques such as the breast cancer pathology helps in the diagnosis…
Baseline wander removal methods for ECG signals: A comparative study
Francisco Perdigon Romero, Liset Vazquez Romaguera, Carlos Román Vázquez-Seisdedos +3
Cardiovascular diseases are the leading cause of death worldwide, accounting for 17.3 million deaths per year. The electrocardiogram (ECG) is a non-invasive technique widely used f…