Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Kein Folientitel
Document related concepts
Transcript
3D Mammography Ernesto Coto Stefan Bruckner Sören Grimm M. Eduard Gröller Institute of Computer Graphics and Algorithms Vienna University of Technology Motivation Breast cancer is the second leading cause of cancer deaths in women today X-Ray Mammography is currently the primary method of early detection Interpretation of Mammograms is difficult Radiologists often use CAD for prompting X-Ray Mammography 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Motivation Capability of X-ray mammography is limited by its 2D representation Other imaging modalities can obtain a full 3D representation of the breast Rendering of MRI Mammography showing cancer 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Introduction Cancer is a disease that causes cells in the body to divide and reproduce abnormally without control Breast cancer refers to a malignant tumor that has developed from breast cells 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Breast Anatomy The breast has two main components: glandular tissue and connective tissue 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Suspicious Regions Calcifications are tiny calcium deposits within the breast tissue Microcalcifications Macrocalcifications Masses Solid Liquid (Cyst) 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Doctors Questions Is there a tumor in the breast? Is the tumor benign or malignant? Is it a mass, a cyst or a microcalcification cluster? What’s the location of the tumor? What’s the size of the tumor? How dense is the breast? What’s the extension of the cancer? 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Imaging Technologies X-Ray Mammography Magnetic Resonance Imaging (MRI) Full-Field Digital Mammography Nuclear Imaging Tomosynthesis Ultrasound X-Ray 3D Mammography Ultrasound MRI TU Wien Institute of Computer Graphics and Algorithms Dynamic Contrast Enhanced MRI A tumor is usually well vascularized due to its strong growth The absorption of contrast-medium in suspicious regions is perceptible Without contrast With contrast Intravenous catheter 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Study of contrast agent’s flow Type I: steady enhancement (straight or curved) Type II: plateau of signal intensity Type III: washout of signal Benign lesion Possible malignancy Strongly suggest malignancy 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Answers using DCE-MRI Is there a tumor in the breast? Segment the contrast agent Is the tumor benign or malignant? Study of contrast agent’s flow Extract features and use them to classify the tumors Is it a mass, a cyst or a microcalcification cluster? Quantify segmented region(s) What’s the location of the tumor? Estimate position of tumor’s center 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Answers using DCE-MRI What’s the size of the tumor? Calculate largest tumor diameter Calculate volume based on segmented voxels How dense is the breast? Segment glandular tissue + quantification 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Answers using DCE-MRI What’s the extension of the cancer? Classify as invasive or non-invasive Non-invasive 3D Mammography Invasive TU Wien Institute of Computer Graphics and Algorithms CAD for DCE-MRI “Interactive Detection and Visualization of Breast Lesions Using Dynamic Contrast Enhanced (DCE) MRI Volumes“, Computerized Medical Imaging and Graphics, Elsevier, July 2004. 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Questions 3D Mammography TU Wien Institute of Computer Graphics and Algorithms Suggestions How can me make this better??? 3D Mammography TU Wien Institute of Computer Graphics and Algorithms
