Visual parameter optimisation for biomedical image processing

BackgroundBiomedical image processing methods require users to optimise input parameters to ensure high-quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output.ResultsWe present a visualisation method that transforms users' ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm.ConclusionsThe visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches.

[1]  Kwan-Liu Ma,et al.  A spreadsheet interface for visualization exploration , 2000, Proceedings Visualization 2000. VIS 2000 (Cat. No.00CH37145).

[2]  William A Link,et al.  Modeling Association among Demographic Parameters in Analysis of Open Population Capture–Recapture Data , 2005, Biometrics.

[3]  Theresa-Marie Rhyne,et al.  Proceedings of the conference on Visualization '98 , 1998 .

[4]  Hans-Christian Hege,et al.  Tuner: Principled Parameter Finding for Image Segmentation Algorithms Using Visual Response Surface Exploration , 2011, IEEE Transactions on Visualization and Computer Graphics.

[5]  Kwan-Liu Ma,et al.  Image graphs-a novel approach to visual data exploration , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[6]  Peter Filzmoser,et al.  Uncertainty‐Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction , 2011, Comput. Graph. Forum.

[7]  Tamara Munzner,et al.  Vismon: Facilitating Analysis of Trade‐Offs, Uncertainty, and Sensitivity In Fisheries Management Decision Making , 2012, Comput. Graph. Forum.

[8]  Sriram Subramanian,et al.  Talking about tactile experiences , 2013, CHI.

[9]  BMC Bioinformatics , 2005 .

[10]  Nirwan Ansari,et al.  Computational Intelligence for Optimization , 1996, Springer US.

[11]  Robert Spence,et al.  The influence explorer , 1995, CHI '95.

[12]  Marc Alexa,et al.  Visualizing time-series on spirals , 2001, IEEE Symposium on Information Visualization, 2001. INFOVIS 2001..

[13]  A. Ruifrok,et al.  Quantification of histochemical staining by color deconvolution. , 2001, Analytical and quantitative cytology and histology.

[14]  Roy A. Ruddle,et al.  Visual Parameter Optimization for Biomedical Image Analysis: A Case Study , 2012, SIGRAD.

[15]  Stefan Wesarg,et al.  Application of Radial Ray Based Segmentation to Cervical Lymph Nodes in CT Images , 2013, IEEE Transactions on Medical Imaging.

[16]  Benjamin B. Bederson,et al.  PhotoMesa: a zoomable image browser using quantum treemaps and bubblemaps , 2001, UIST '01.

[17]  J. Hartigan.  Printer graphics for clustering , 1975 .

[18]  Roy A. Ruddle,et al.  Visualization of Parameter Space for Image Analysis , 2011, IEEE Transactions on Visualization and Computer Graphics.

[19]  Stefan Wesarg,et al.  Visual Analytics for model-based medical image segmentation: Opportunities and challenges , 2013, Expert Syst. Appl..

[20]  Torsten Möller,et al.  ParaGlide: Interactive Parameter Space Partitioning for Computer Simulations , 2011, IEEE Transactions on Visualization and Computer Graphics.

[21]  Wolfgang Berger,et al.  Eurographics/ Ieee-vgtc Symposium on Visualization 2010 Hypermoval: Interactive Visual Validation of Regression Models for Real-time Simulation , 2022 .

[22]  Tamara Munzner,et al.  Design Study Methodology: Reflections from the Trenches and the Stacks , 2012, IEEE Transactions on Visualization and Computer Graphics.

[23]  Stefan Bruckner,et al.  Result-Driven Exploration of Simulation Parameter Spaces for Visual Effects Design , 2010, IEEE Transactions on Visualization and Computer Graphics.

[24]  Matthew O. Ward,et al.  Exploring N-dimensional databases , 1990, Proceedings of the First IEEE Conference on Visualization: Visualization `90.

[25]  Eduard Gröller,et al.  Cupid: Cluster-Based Exploration of Geometry Generators with Parallel Coordinates and Radial Trees , 2014, IEEE Transactions on Visualization and Computer Graphics.

[26]  Ramana Rao,et al.  The table lens: merging graphical and symbolic representations in an interactive focus + context visualization for tabular information , 1994, CHI '94.

[27]  Ben Shneiderman,et al.  Visualization methods for personal photo collections: browsing and searching in the PhotoFinder , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[28]  Anne E Carpenter,et al.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes , 2006, Genome Biology.

[29]  Thomas Schultz,et al.  Open-Box Spectral Clustering: Applications to Medical Image Analysis , 2013, IEEE Transactions on Visualization and Computer Graphics.

[30]  Stefan Bruckner,et al.  Visual Parameter Space Analysis: A Conceptual Framework , 2014, IEEE Transactions on Visualization and Computer Graphics.

[31]  Paul A. Beardsley,et al.  Design galleries: a general approach to setting parameters for computer graphics and animation , 1997, SIGGRAPH.

[32]  Stefan Wesarg,et al.  Opening up the “black box” of medical image segmentation with statistical shape models , 2013, The Visual Computer.

[33]  Cláudio T. Silva,et al.  Managing the Evolution of Dataflows with VisTrails , 2006, 22nd International Conference on Data Engineering Workshops (ICDEW'06).

[34]  James R. Miller,et al.  Conference Companion on Human Factors in Computing Systems , 1995, CHI 1995.

[35]  Miriah Meyer,et al.  Designing Visualizations For Biological Data , 2013, Leonardo.

[36]  Chinyere Okechi Onwubiko,et al.  Introduction to engineering design optimization , 1999 .

[37]  Tamara Munzner,et al.  LiveRAC: interactive visual exploration of system management time-series data , 2008, CHI.

[38]  Denis Gracanin,et al.  Interactive Visual Steering - Rapid Visual Prototyping of a Common Rail Injection System , 2008, IEEE Transactions on Visualization and Computer Graphics.

[39]  Anne E Carpenter,et al.  Visualization of image data from cells to organisms , 2010, Nature Methods.