Image Reconstruction in a Manifold of Image Patches: Application to Whole-Fetus Ultrasound Imaging

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

7 Citations (Scopus)

Abstract

We propose an image reconstruction framework to combine a large number of overlapping image patches into a fused reconstruction of the object of interest, that is robust to inconsistencies between patches (e.g. motion artefacts) without explicitly modelling them. This is achieved through two mechanisms: first, manifold embedding, where patches are distributed on a manifold with similar patches (where similarity is defined only in the region where they overlap) closer to each other. As a result, inconsistent patches are set far apart in the manifold. Second, fusion, where a sample in the manifold is mapped back to image space, combining features from all patches in the region of the sample. For the manifold embedding mechanism, a new method based on a Convolutional Variational Autoencoder (β -VAE) is proposed, and compared to classical manifold embedding techniques: linear (Multi Dimensional Scaling) and non-linear (Laplacian Eigenmaps). Experiments using synthetic data and on real fetal ultrasound images yield fused images of the whole fetus where, in average, β -VAE outperforms all the other methods in terms of preservation of patch information and overall image quality.

Original languageEnglish
Title of host publicationMachine Learning for Medical Image Reconstruction - 2nd International Workshop, MLMIR 2019, held in Conjunction with MICCAI 2019, Proceedings
EditorsFlorian Knoll, Andreas Maier, Daniel Rueckert, Jong Chul Ye
PublisherSPRINGER
Pages226-235
Number of pages10
ISBN (Print)9783030338428
DOIs
Publication statusPublished - 24 Oct 2019
Event2nd International Workshop on Machine Learning for Medical Image Reconstruction, MLMIR 2019 held in Conjunction with 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 17 Oct 201917 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11905 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Machine Learning for Medical Image Reconstruction, MLMIR 2019 held in Conjunction with 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
Country/TerritoryChina
CityShenzhen
Period17/10/201917/10/2019

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