1.2k citations · 1.7k across the 23 of their papers we have counts for
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M-GenSeg: Domain Adaptation For Target Modality Tumor Segmentation With Annotation-Efficient Supervision
Malo Alefsen de Boisredon d'Assier, Eugene Vorontsov, Samuel Kadoury
Automated medical image segmentation using deep neural networks typically requires substantial supervised training. However, these models fail to generalize well across different i…
3D B-mode ultrasound speckle reduction using deep learning for 3D registration applications
Hongliang Li, Tal Mezheritsky, Liset Vazquez Romaguera +1
Ultrasound (US) speckles are granular patterns which can impede image post-processing tasks, such as image segmentation and registration. Conventional filtering approaches are comm…
Spatiotemporal motion prediction in free-breathing liver scans via a recurrent multi-scale encoder decoder
Liset Vázquez Romaguera, Rosalie Plantefève, Samuel Kadoury
In this work we propose a multi-scale recurrent encoder-decoder architecture to predict the breathing induced organ deformation in future frames. The model was trained end-to-end f…
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problem with results session, numbers are incorrect, theoretical thinking is no longer valid
Evaluation of MRI to ultrasound registration methods for brain shift correction: The CuRIOUS2018 Challenge
Yiming Xiao, Hassan Rivaz, Matthieu Chabanas +13
In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets…
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…