Healthcare @ IBM Research | Australia - Multimedia Analytics
Multimedia Analytics @ IBM Research | Australia
Our researchers have expertise in video and image processing, data mining, pattern recognition and information retrieval. We feature the following projects to demonstrate our multi-media analytics capabilities.
Medical Sieve Grand Challenge
The Medical Sieve is a diagnostic clinical descision-support tool with advanced textual and visual reasoning capabilities. As an image-guided informatics system, the Medical Seive acts like a filter, identifying and collating the clinical information required by physicians for patient diagnosis and treatment planning. This filtering employs sophisticated medical image processing, pattern recognition and machine learning techniques guided by advanced clinical knowledge. It uses feature extraction and cognitive methods to automatically classify image content and retrieve similar patient cases based on image features.
Collaborators: IBM Research - Almaden and IBM Research - Haifa
Computer-Aided Melanoma Diagnosis
Melanoma (skin cancer) is one of the most common and deadly cancers world-wide, and has steadily increased in incidence over the last few decades. Diagnosis is a very subjective process, and consequently there is a lack of standardisation between institutions, between clinicians at the same institutions and even for different patients who see the same clinicain. This leads to a poor quality of treatment in areas where expertise are limited. IBM Research is collaborating with Memorial Sloan-Kettering Cancer Centre to develop a system enabling standardised, early detection of melanoma. We automate the classification of skin lesions by application of image processing and machine learning algorithms to multi-modal skin imaging data, in combination with global, local and patient-level information, a-priori disease information, and temporal analytics.
Modified. Original Image Paul Irish
Collaborators: IBM T. J. Watson Research Center and Memorial Sloan-Kettering Cancer Centre
M. Abedini, N. Codella, J. Connell, R. Garnavi, M. Merler, S. Pankanti, J. R. Smith, and T. Syeda-Mahmood. A generalized framework for medical image classification and recognition IBM Journal of Research and Development vol. 59, no. 2/3 2015 (in press)
Q. Chen, M. Abedini, R. Garnavi, X. Liang IBM Research Australia at LifeCLEF2014: Plant Identification Task, LifeCLEF2014 In proceeding of CLEF2014.
M. Abedini, L.Cao, N. Codella, J. H. Connell, R. Garnavi, A. Geva, M. Merler, Q. Nguyen, S. U. Pankanti, J. R. Smith, X. Sun, and A. Tzadok IBM Research at ImageCLEF 2013 Medical Tasks American Medical Informatics Association, 2013