250 citations · 531 across the 23 of their papers we have counts for
5 papers · 1 filter
Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects
Nikos Chrisochoides, Andrey Fedorov, Yixun Liu +10
Current neurosurgical procedures utilize medical images of various modalities to enable the precise location of tumors and critical brain structures to plan accurate brain tumor re…
Advancing Intra-operative Precision: Dynamic Data-Driven Non-Rigid Registration for Enhanced Brain Tumor Resection in Image-Guided Neurosurgery
Nikos Chrisochoides, Andriy Fedorov, Fotis Drakopoulos +9
During neurosurgery, medical images of the brain are used to locate tumors and critical structures, but brain tissue shifts make pre-operative images unreliable for accurate remova…
Deep reinforcement learning in medical imaging: A literature review
S. Kevin Zhou, Hoang Ngan Le, Khoa Luu +2
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which learns a sequence of actions that maximizes the expected reward, with the representative powe…
Combining Bayesian and Deep Learning Methods for the Delineation of the Fan in Ultrasound Images
Hind Dadoun, Hervé Delingette, Anne-Laure Rousseau +2
Ultrasound (US) images usually contain identifying information outside the ultrasound fan area and manual annotations placed by the sonographers during exams. For those images to b…
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…