2 citations · 2 across the 1 of their papers we have counts for
3 papers
Anatomically Consistent Segmentation of Organs at Risk in MRI with Convolutional Neural Networks
Pawel Mlynarski, Hervé Delingette, Hamza Alghamdi +2
Planning of radiotherapy involves accurate segmentation of a large number of organs at risk, i.e. organs for which irradiation doses should be minimized to avoid important side eff…
Deep Learning with Mixed Supervision for Brain Tumor Segmentation
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi +1
Most of the current state-of-the-art methods for tumor segmentation are based on machine learning models trained on manually segmented images. This type of training data is particu…
3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi +1
We present an efficient deep learning approach for the challenging task of tumor segmentation in multisequence MR images. In recent years, Convolutional Neural Networks (CNN) have…