26 citations · 87 across the 21 of their papers we have counts for
4 papers · 1 filter
MRI Super-Resolution using Multi-Channel Total Variation
Mikael Brudfors, Yael Balbastre, Parashkev Nachev +1
This paper presents a generative model for super-resolution in routine clinical magnetic resonance images (MRI), of arbitrary orientation and contrast. The model recasts the recove…
A Modality-Adaptive Method for Segmenting Brain Tumors and Organs-at-Risk in Radiation Therapy Planning
Mikael Agn, Per Munck af Rosenschöld, Oula Puonti +7
In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method comb…
An Algorithm for Learning Shape and Appearance Models without Annotations
John Ashburner, Mikael Brudfors, Kevin Bronik +1
This paper presents a framework for automatically learning shape and appearance models for medical (and certain other) images. It is based on the idea that having a more accurate s…
Diffeomorphic brain shape modelling using Gauss-Newton optimisation
Yaël Balbastre, Mikael Brudfors, Kevin Bronik +1
Shape modelling describes methods aimed at capturing the natural variability of shapes and commonly relies on probabilistic interpretations of dimensionality reduction techniques s…