Depliant ABCDE bis - COMUNICHIAMO | In questo spazio i …€¦ · · 2012-05-072012-05-07 ·...
Transcript of Depliant ABCDE bis - COMUNICHIAMO | In questo spazio i …€¦ · · 2012-05-072012-05-07 ·...
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Introduction Breast cancer is the second cause of cancer death among women. About 1 million of new cases every year appear in the world. About 25% of them lead to the death of the patient.
The most efficient solution is the use of an effective screening strategy.
At present, mammography is the most used method for early detection of tumoral signs. The advantages of this approach are: The mammography is inexpensive with respect to other techniques. The mammography is not invasive. The mammography needs small X‐ray dose to produce suitable images.
On the contrary, mammographic images are very difficult to interpret also by expert
radiologists.
Analog
mammography
Indirect digital
mammography
Direct digital
mammography
The mistakes occurring in the radiologist analyses of mammograms are often due to human factors such as the difficulty to appreciate very low contrast objects having ill defined margins, or very small details.
About 10 – 20 % of lesions are not diagnosed.
For this reason, it is possible to improve the patients survival rate with a second reader that evaluates the mammographic image independently.
The purpose of a CADx (Computer Aided Diagnosis) system is to take place of the second human reader to save time and costs but never to substitute the first radiologist in the image interpretation.
ABCDE (Assisted Breast Cancer Diagnosis Environment) is a project developed at the research group at the University of Rome Tor Vergata.
ABCDE is a CADx able to assist radiologist during mammogram analysis as a second reader. It is a complete set of tools including: Reading of mammographic images Exploring ROIs (Regions Of Interest) Contrast enhancement and noise reduction Automatic identification of suspicious zones Features extraction of suspicious signs Classification and risk degree assignment
Reading of images ABCDE can acquire both digital and analog mammographic images.
DICOM (Digital Imaging and COmmunications in Medicine) is the standard de facto in medical images recording. ABCDE supports it (and its extensions such as the GSPS, Grayscale Softcopy Presentation State), so that images can be directly acquired from commonly used hospital digital supports, even through a useful DICOMDIR (database file of the stored images in a tree form catalogued in patients, studies, series, and images) explorer. Analog screen film mammograms can be acquired by a proper scanner (even calibrated in order to compensate loss of linearity).
Other kind of images can be acquired by a proper procedure that converts the
original image in the native format preserving all the image properties.
Denoising and contrast enhancement The radiologist can inspect suspicious regions selecting a ROI viewing its content enlarged in a separate window. Contrast enhancement permits to inspect the selected ROI with a better contrast reducing noise amount and preserving any detail of the original image. This procedure uses sophisticated proprietary algorithms in order to obtain optimized processing and so clear and sharp images.
Automatic identification The automatic identification procedure suggests to radiologist several suspicious zones that could contain a tumoral lesion such as a mass or a microcalcifications cluster.
The doctor selects one or more regions in which to perform a deep analysis consisting of:
Lesion segmentation Features extraction Risk degree assignment
Lesion inspection In the case of a mass, the procedure
performs a boundary extraction driven by the radiologist that accepts the most probable contour, extracts a set of mathematical features (both geometrical and textural (Haralick and Laws), evaluates those features and assigns to the lesion a risk degree.
Taking into account the risk degree assigned by ABCDE, the radiologist states the diagnosis.
The assessment that the doctor can carry out with ABCDE is compliant with ACR BIRADS© standard.
References The procedure has been tested on the DDSM (Digital Database for Screening Mammography, University of South Florida). This database contains 2620 cases available in 43 volumes (Normal, Cancer, and Benign) and CC and MLO images for each breast assessed by radiologists.
The results of the research have been published on the most important international scientific journals and presented to many conferences.
The complete list can be found on the research group web site http://simplify.it.