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Imaging Tools for Cancer Research

The goal of our work in Biomedical Imaging is two-fold: One, to develop advanced imaging tools for biomedical research in partnership with the National Cancer Institute and other organizations. Secondly, to conduct research in Content Based Image Retrieval (CBIR) to index and retrieve medical images by image features (e.g., shape, color and texture), augmented by textual features as well. This work includes the development of the CervigramFinder for retrieval of uterine cervix images by image features, SPIRS for retrieval of digitized x-ray images of the spine from NHANES II and a distributed global system (SPIRS-IRMA) for image retrieval by both high-level and detailed features of medical images, in collaboration with Aachen University, Germany.

CBIR is also an aspect of the Image Text Indexing (ITI) project that seeks to automatically index illustrations in medical articles by processing text in figure captions and mentions in the article, as well as image features in the illustrations.

Mrabet Y, Kilicoglu H, Demner-Fushman D. Unsupervised Ranking of Knowledge Bases for Named Entity Recognition. 22nd European Conference on Artificial Intelligence (ECAI 2016), The Hague, Holland, Aug 29 - Sep 02, 2016.
Candemir S, Jaeger S, Antani S, Bagci U, Folio LR, Xu Z, Thoma G. Atlas-based rib-bone detection in chest X-rays. Comput Med Imaging Graph. 2016 Jul;51:32-9. doi: 10.1016/j.compmedimag.2016.04.002. Epub 2016 Apr 13.
Guo P, Banerjee K, Stanley RJ, Long LR, Antani SK, Thoma GR, Frazier SR, Moss RH, Stoecker WV. Nuclei-Based Features for Uterine Cervical Cancer Histology Image Analysis with Fusion-based Classification. DOI 10.1109/JBHI.2015.2483318 IEEE Journal of Biomedical and Health Informatics
Xu T, Xin C, Long LR, Antani SK, Xue Z, Kim E, Huang X. A New Image Data Set and Benchmark for Cervical Dysplasia Classification Evaluation. Machine Learning in Medical Imaging: 6th International Workshop, MLMI 2015, LNCS 9352, pp. 26–35, 2015. DOI: 10.1007/978-3-319-24888-2 4.
Rahman MM, Antani SK, Demner-Fushman D, Thoma GR. Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval. J Med Imaging (Bellingham). 2015 Oct;2(4):046502. doi: 10.1117/1.JMI.2.4.046502. Epub 2015 Dec 30.
Ruiz A, Allette K, Francis D, Lamping E, Jaeger S, Folio L, Apolo A. Patterns of soft tissue metastasis in patients with urothelial carcinoma using tumor volume heatmaps [Poster]. NIH Summer Research Program Poster Day, Aug 6, 2015
Vajda S, Rangoni Y, Cecotti H. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition. Pattern Recognit Lett. 2015 Jun 1;58:23-28.
Xu T, Huang X, Kim E, Long LR, Antani SK. Multi-test cervical cancer diagnosis with missing data estimation. Proc. SPIE. 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94140X. (March 20, 2015) doi: 10.1117/12.2080871.
Xue Z, You D, Chachra S, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Extraction of endoscopic images for biomedical figure classification. Proc. SPIE. 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180P. (March 17, 2015) doi: 10.1117/12.2081033.
Candemir S, Antani SK, Jaeger SR, Thoma GR. Lung boundary detection in pediatric chest x-rays. Proc. SPIE. 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180Q. (March 17, 2015) doi: 10.1117/12.2081060.