@inproceedings{6c685f5fadfa414285e4cb27ba4c64a2,
title = "SparkGIS: Efficient comparison and evaluation of algorithm results in tissue image analysis studies",
abstract = "Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison of multiple results, and facilitate algorithm sensitivity studies. The sizes of images and analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present SparkGIS, a distributed, in-memory spatial data processing framework to query, retrieve, and compare large volumes of analytical image result data for algorithm evaluation. Our approach combines the in-memory distributed processing capabilities of Apache Spark and the efficient spatial query processing of Hadoop-GIS. The experimental evaluation of SparkGIS for heatmap computations used to compare nucleus segmentation results from multiple images and analysis runs shows that SparkGIS is efficient and scalable, enabling algorithm evaluation and algorithm sensitivity studies on large datasets.",
author = "Furqan Baig and Mudit Mehrotra and Hoang Vo and Fusheng Wang and Joel Saltz and Tahsin Kurc",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 1st International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2015 and Workshop on Big-Graphs Online Querying, Big-O(Q) 2015 held in conjunction with 41st International Conference on Very Large Data Bases, VLDB 2015 ; Conference date: 31-08-2015 Through 04-09-2015",
year = "2016",
doi = "10.1007/978-3-319-41576-5\_10",
language = "English",
isbn = "9783319415758",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "134--146",
editor = "Arijit Khan and Gang Luo and Chunhua Weng and Fusheng Wang and Prasenjit Mitra and Cong Yu",
booktitle = "Biomedical Data Management and Graph Online Querying - VLDB 2015 Workshops, Big-O(Q) and DMAH, Revised Selected Papers",
}