Leveraging random forests for interactive exploration of large histological images

Loïc Peter, Diana Mateus, Pierre Chatelain, Noemi Schworm, Stefan Stangl, Gabriele Multhoff, Nassir Navab

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

5 Zitate (Scopus)

Abstract

The large size of histological images combined with their very challenging appearance are two main difficulties which considerably complicate their analysis. In this paper, we introduce an interactive strategy leveraging the output of a supervised random forest classifier to guide a user through such large visual data. Starting from a forest-based pixelwise estimate, subregions of the images at hand are automatically ranked and sequentially displayed according to their expected interest. After each region suggestion, the user selects among several options a rough estimate of the true amount of foreground pixels in this region. From these one-click inputs, the region scoring function is updated in real time using an online gradient descent procedure, which corrects on-the-fly the shortcomings of the initial model and adapts future suggestions accordingly. Experimental validation is conducted for extramedullary hematopoesis localization and demonstrates the practical feasibility of the procedure as well as the benefit of the online adaptation strategy.

OriginalspracheEnglisch
TitelMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
Herausgeber (Verlag)Springer Verlag
Seiten1-8
Seitenumfang8
AuflagePART 1
ISBN (Print)9783319104034
DOIs
PublikationsstatusVeröffentlicht - 2014
Veranstaltung17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, USA/Vereinigte Staaten
Dauer: 14 Sept. 201418 Sept. 2014

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NummerPART 1
Band8673 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

Konferenz17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
Land/GebietUSA/Vereinigte Staaten
OrtBoston, MA
Zeitraum14/09/1418/09/14

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