Mammography with statistical image processing (MSIP): Our research at the department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institute, is concerned with the analysis of digital mammography images. The general aim of this project is to investigate in detail the relationship between some patterns present in the breast and cancer risk and prognosis in a populations-based study of breast cancer as well as in a mammography screening-based study of breast cancer. The work involves both methodological as well as applied collaborative projects with medical researchers.
More explicitly, I am working on extracting additional biomarkers, apart from mammographic density, from mammographic images which can boost risk prediction of breast cancer. I am also involved in the automation of the semi-automatic software Cumulus on the digitised analog screen films for area-based density measurement and also on the automation of volumetric mammography density on processed full field digital mammography (FFDM).
The software package that implements the below algorithms can be ordered now free of charge. Please fill and sign the following agreement letter and return it (scanned) to the email shown in the document.
- Abbas Cheddad, Kamila Czene, John Shepherd, Jingmei Li, Per Hall, Keith Humphreys, (2014). Enhancement of mammographic density measures in breast cancer risk prediction. Cancer Epidemiology, Biomarkers & Prevention (CEBP), 23(7)(2014) 1314-1323. American Association for Cancer Research. PMID: 24722754.
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Reviewer's comment: "This manuscript presents an interesting and novel approach to enhance mammographic density assessment from 2-dimensional images. It has been long been considered a weakness that the common assessment methods using film mammograms ignore the third dimension of breast thickness. Therefore, this paper makes a new contribution to the field of mammographic density research..." .
- Abbas Cheddad, Kamila Czene, Mikael Eriksson, Jingmei Li, Douglas Easton, Per Hall and Keith Humphreys (2014). Area and volumetric density estimation in processed full-field digital mammograms for risk assessment of breast cancer. PLoS One,9(10)(2014) 1-10.Get the PDF
- Holm J, Humphreys K, Li J, Ploner A, Cheddad A, Eriksson M, Törnberg S, Hall P, Czene K. Risk factors and tumor characteristics of interval cancers by mammographic density. Journal of Clinical Oncology,33(9)(2015)1030-1037. PMID: 25646195.Get the PDF
- Cheddad A, Czene K, Hall P and Humphreys K. Pectoral muscle attenuation as a marker for breast cancer risk in Full Field Digital Mammography..Cancer Epidemiology, Biomarkers & Prevention (CEBP),24(6)(2015) 985–991. PMID: 25870223.Get the PDF
- Fredrik Strand, Keith Humphreys, Abbas Cheddad, Sven Törnberg, Edward Azavedo, John Shepherd, Per Hall, Kamila Czene. Novel mammographic image features differentiate between interval and screen-detected breast cancer: a case-case study..Breast Cancer Research, 18(1)100, 2016.PMID: 27716311.Get the PDF
- Ola Spjuth, Andreas Karlsson, Mark Clements, Keith Humphreys, Emma Ivansson, Jim Dowling, Martin Eklund, Alexandra Jauhiainen, Kamila Czene, Henrik Grönberg, Pär Sparén, Fredrik Wiklund, Abbas Cheddad, ţorgerđur Pálsdóttir, Mattias Rantalainen, Linda Abrahamsson, Erwin Laure, Jan-Eric Litton, and Juni Palmgren. E-Science technologies in a workflow for personalized medicine using cancer screening as a case study..Journal of the American Medical Informatics Association, 0(0), 2017, 1-8.PMID: 28444384.Get the PDF