title: Leveraging random forests for interactive exploration of large histological images.
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.
authors.forename: Loïc
authors.initials: L
authors.lastname: Peter
authors.forename: Diana
authors.initials: D
authors.lastname: Mateus
authors.forename: Pierre
authors.initials: P
authors.lastname: Chatelain
authors.forename: Noemi
authors.initials: N
authors.lastname: Schworm
authors.forename: Stefan
authors.initials: S
authors.lastname: Stangl
authors.forename: Gabriele
authors.initials: G
authors.lastname: Multhoff
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
mesh_terms: D000465:Algorithms; D001773:Blood Cells / Q000166:cytology* / Q000502:physiology*; D002478:Cells, Cultured; D003627:Data Interpretation, Statistical; D006411:Hematopoiesis, Extramedullary / Q000502:physiology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008853:Microscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface