Publications

@article{Hobson20163,
title = {Computer Aided Diagnosis for Anti-Nuclear Antibodies HEp-2 images: Progress and challenges},
author = {Peter Hobson and Brian C. Lovell and Gennaro Percannella and Alessia Saggese and Mario Vento and Arnold Wiliem},
url = {http://www.sciencedirect.com/science/article/pii/S0167865516301374},
doi = {http://dx.doi.org/10.1016/j.patrec.2016.06.013},
issn = {0167-8655},
year = {2016},
date = {2016-01-01},
journal = {Pattern Recognition Letters},
volume = {82, Part 1},
pages = {3 - 11},
abstract = {The Anti-Nuclear Antibodies (ANA) test using Human Epithelial (HEp-2) cells has been the gold standard to identify the presence of Connective Tissue Diseases (CTD) such us Systemic Lupus Erythomatus (SLE). As the ANA test is time consuming, labor intensive and subjective, there has been an on-going effort to develop image-based Computer Aided Diagnosis (CAD) systems. This paper discusses the current progress and challenges in this field and will highlight areas which require more attention.},
note = {Pattern recognition Techniques for Indirect Immunofluorescence Images Analysis},
keywords = {Computer Aided Diagnoses},
pubstate = {published},
tppubtype = {article}
}

@article{Hobson201612,
title = {HEp-2 staining pattern recognition at cell and specimen levels: Datasets, algorithms and results},
author = {Peter Hobson and Brian C. Lovell and Gennaro Percannella and Alessia Saggese and Mario Vento and Arnold Wiliem},
url = {http://www.sciencedirect.com/science/article/pii/S0167865516301751},
doi = {http://dx.doi.org/10.1016/j.patrec.2016.07.013},
issn = {0167-8655},
year = {2016},
date = {2016-01-01},
journal = {Pattern Recognition Letters},
volume = {82, Part 1},
pages = {12 - 22},
abstract = {The Indirect Immunofluorescence (IIF) protocol applied on Human Epithelial type 2 (HEp-2) cells is the current gold standard for the Antinuclear Antibody (ANA) test. The formulation of the diagnosis requires the visual analysis of a patient’s specimen under a fluorescence microscope in order to recognize the cells’ staining pattern which could be related to a connective tissue disease. This analysis is time consuming and error prone, thus in the recent past we have witnessed a growing interest in the pattern recognition scientific community directed at the development of methods for supporting this complex task. The main driver of the interest towards this problem is represented by the series of international benchmarking initiatives organized in the last four years that allowed dozens of research groups to propose innovative methodologies for HEp-2 cells’ staining pattern classification. In this paper we update the state of the art on HEp-2 cells and specimens classification, by analyzing the performance achieved by the methods participating the contest on Performance Evaluation of IIF Image Analysis Systems, hosted by the 22nd edition of the International Conference on Pattern Recognition ICPR 2014, and to the Executable Thematic Special Issue of Pattern Recognition Letters on Pattern Recognition Techniques for IIF Images Analysis, and by highlighting the trends in the design of the best performing methods.},
note = {Pattern recognition Techniques for Indirect Immunofluorescence Images Analysis},
keywords = {Computer Aided Diagnoses},
pubstate = {published},
tppubtype = {article}
}