activity
20152021
most citedJoint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

37 citations · 62 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Uncertainty-Aware Annotation Protocol to Evaluate Deformable Registration Algorithms

Loic Peter, Daniel C. Alexander, Caroline Magnain +1

Landmark correspondences are a widely used type of gold standard in image registration. However, the manual placement of corresponding points is subject to high inter-user variabil…

cs.CV2020

Active Annotation of Informative Overlapping Frames in Video Mosaicking Applications

Loic Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir +4

Video mosaicking requires the registration of overlapping frames located at distant timepoints in the sequence to ensure global consistency of the reconstructed scene. However, ful…

cs.CV2018★ 18 cited

Retrieval and Registration of Long-Range Overlapping Frames for Scalable Mosaicking of In Vivo Fetoscopy

Loïc Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir +5

Purpose: The standard clinical treatment of Twin-to-Twin Transfusion Syndrome consists in the photo-coagulation of undesired anastomoses located on the placenta which are responsib…

cs.CV2018★ 37 cited

Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

Juan Eugenio Iglesias, Marc Modat, Loic Peter +6

Nonlinear registration of 2D histological sections with corresponding slices of MRI data is a critical step of 3D histology reconstruction. This task is difficult due to the large…

cs.CV2017

A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data

Benjamín Gutiérrez, Loïc Peter, Tassilo Klein +1

With the availability of big medical image data, the selection of an adequate training set is becoming more important to address the heterogeneity of different datasets. Simply inc…

cs.CV2016

Hands-Free Segmentation of Medical Volumes via Binary Inputs

Florian Dubost, Loic Peter, Christian Rupprecht +2

We propose a novel hands-free method to interactively segment 3D medical volumes. In our scenario, a human user progressively segments an organ by answering a series of questions o…