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Computer-Aided Identification of Microcalcifications using Matlab

Computer-Aided Identification of Microcalcifications using Matlab. BME 316 Angela Bookwalter Kelly Braun. First--Some Facts. 1 out of every 8 women will be diagnosed with breast cancer Family history plays a very important role in determining whether a women is at risk for breast cancer.

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Computer-Aided Identification of Microcalcifications using Matlab

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  1. Computer-Aided Identification of Microcalcifications using Matlab BME 316 Angela Bookwalter Kelly Braun

  2. First--Some Facts • 1 out of every 8 women will be diagnosed with breast cancer • Family history plays a very important role in determining whether a women is at risk for breast cancer. • Each year more than 180,000 new cases of breast cancer are diagnosed in the US. It is the leading cause of death for women between the ages of 35 and 54. • Mammograms find invasive breast cancer in about 75% of the women who have breast cancer under the age of 50, mammograms can miss cancer

  3. What Is Breast Cancer? • Uncontrolled growths of abnormal cells • Cancerous tumor that develops in the breast • 80% of women find a lump in breast - most common symptom • 20-25% of all breast cancers are associated with some form of microcalcifications

  4. Mammograms • special type of x-ray imaging using low dose x-ray; high contrast, high resolution film • Breast compression is necessary in order to image maximum amount of tissue, reduce x-ray scatter, and immobilize the breast. • Best way to find breast cancer in its earliest stages-find microcalcification clusters

  5. Microcalcifications • Microscopic grains of calcium produced by the cells as the result of some benign or malignant process, such as the rest products of broken down cells, a cyst or milk. • Calcifications produced by cancer cells are generally granular or irregular in shape and appear in clusters. • Have much higher attenuation than surrounding tissue, absorb more radiation.

  6. Finding Microcalcifications • In some mammograms they are visible as nearly white spots on dark gray background and in others they are visible as brighter gray spots on a slightly darker gray background, depending on the grayscale.

  7. Cluster of Microcalcifications • This image of a breast shows a cluster of many microcalcifications

  8. Branching Microcalcifications • Left Breast • This mammogram depicts irregular clustered branching calcifications in the sub-areolar area. • This branching extends over 30 mm. • Left LMO

  9. Cancerous Tumor • This mammogram depicts the appearance of a spiculated lesion in the upper outer quadrant of the right breast typical of carcinoma. • The mass in this image measures 3 cm. • This patient discovered a lump in her breast. • Craniocaudal view

  10. Digital Screening • Image analysis technique used for the automatic detection, segmentation, numerical analysis and classification of microcalcifications • Digital mammography is "The most fertile territory for major advances in the detection and diagnosis of minimal breast cancers." • In a digital mammographic system the film/screen cassette is replaced by a phosphor screen which detects the x-ray photons leaving the breast. The phosphor screen converts the x-ray photons into light which is transferred through a fiber optical reducer to the CCD (Charged Coupled Device) detector. A 50mm by 50mm phosphor screen image is reduced to a 25mm by 25mm CCD light sensor. The matrix of a typical CCD is 1024 by 1024 therefore each pixel can resolve 0.05mm. The CCD converts the incident light into a digitized analogue signal and this signal is displayed onto a computer monitor. Rather than reaching an optical density of 1.4, the exposure is terminated when a sufficient signal to noise ratio is achieved. • This would reduce the discomfort to the patient as it would reduce the procedure time • Digital imaging of the breast produces a much wider and more linear dynamic range and is therefore more ideal for radiological dense breast types. • http://www.ozemail.com.au/~glensan/digmam.htm

  11. Objective • Develop a program in Matlab which will find individual microcalcifications in a breast image and: • Display black and white image highlighting microcalcifications as white points. • Count the microcalcifications. • Pick out clusters. • Give average distances between individual microcalcifications.

  12. Matlab Programming • Scans image • Issues gray scale values of 1 or 0, 1 for the microcalcifications and 0 for background • reads the image into an array based on 1’s and 0’s • finds clusters of 1’s

  13. Results

  14. Discussion

  15. Conclusion

  16. fty

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