8 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…
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problem with results session, numbers are incorrect, theoretical thinking is no longer valid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,…