Advancing Intra-operative Precision: Dynamic Data-Driven Non-Rigid Registration for Enhanced Brain Tumor Resection in Image-Guided Neurosurgery

no code implementations • 18 Aug 2023 • Nikos Chrisochoides, Andriy Fedorov, Fotis Drakopoulos, Andriy Kot, Yixun Liu, Panos Foteinos, Angelos Angelopoulos, Olivier Clatz, Nicholas Ayache, Peter M. Black, Alex J. Golby, Ron Kikinis

Our review explores a specific NRR method for registering brain MRI during image-guided neurosurgery and examines various strategies for improving the accuracy and speed of the NRR method.

Distributed Computing

ModelHub.AI: Dissemination Platform for Deep Learning Models

no code implementations • 26 Nov 2019 • Ahmed Hosny, Michael Schwier, Christoph Berger, Evin P Örnek, Mehmet Turan, Phi V Tran, Leon Weninger, Fabian Isensee, Klaus H. Maier-Hein, Richard McKinley, Michael T Lu, Udo Hoffmann, Bjoern Menze, Spyridon Bakas, Andriy Fedorov, Hugo JWL Aerts

Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among others.

Benchmarking

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

no code implementations • 25 Feb 2017 • Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles R. G. Guttmann, Frank-Erik de Leeuw, Clare M. Tempany, Bram van Ginneken, Andriy Fedorov, Purang Abolmaesumi, Bram Platel, William M. Wells III

In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?

Domain Adaptation Lesion Segmentation +1