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New AI-Based Methods to Analyze Microscopy Images of Breast Cancer Tissue


New AI-Based Methods to Analyze Microscopy Images of Breast Cancer Tissue
Written by AZoRoboticsMay 11 2021
The World Health Organization reports that, in recent times, breast cancer has exceeded lung cancer to become the most common type of cancer worldwide.
AI algorithms performed well on easier breast cancer image patches, like these. Image Credit: Petrick et al., doi 10.1117/1.JMI.8.3.034501
The BreastPathQ Challenge was started at SPIE Medical Imaging 2019 to progress the fight against breast cancer and to help develop a computer-aided diagnosis for evaluating breast cancer pathology.
The participants of BreastPathQ Challenge were given a task to design an automated technique for examining microscopy images of breast tissue and rating them as per their tumor cell content, to offer a trustworthy assessment score. ....

Nicholas Petrick , Division Of Imaging , Software Reliability , Radiological Health , International Effort , World Health Organization , Breastpathq Challenge Group , Breastpathq Challenge , Medical Imaging , Grand Challenge , நிக்கோலஸ் பெட்ரிக் , பிரிவு ஆஃப் இமேஜிங் , மென்பொருள் நம்பகத்தன்மை , கதிரியக்கவியல் ஆரோக்கியம் , சர்வதேச முயற்சி , உலகம் ஆரோக்கியம் ஆர்கநைஸேஶந் , மருத்துவ இமேஜிங் , மாபெரும் சவால் ,

Breast Cancer: CT-Planning Scans Can Inform Cardio-Onco Strategy


May 10, 2021
CAC score may guide breast ca Tx and CVD prevention
The risk of cardiovascular disease, particularly coronary artery disease, among breast cancer survivors is well-known, but a study from Dutch researchers suggests that CT scans used to plan breast cancer treatment regimens can also measure coronary artery calcium (CAC), and those CAC scores can be used to reduce the heart disease burden seen in breast cancer survivors.
The concept provides a real-world example of the interface between oncology and cardiology, which has given rise to cardio-onco subspecialists, and it offers the added advantage of simplicity: CAC scores can be “automatically extracted from planning CT scans using a deep learning algorithm.” ....

Peggy Peck , Roxanne Gal , Division Of Imaging , Dutch Cancer Society , Department Of Radiotherapy University Medical Center Utrecht , Dutch Cancer , பெக்கி பெக் , பிரிவு ஆஃப் இமேஜிங் , டச்சு புற்றுநோய் சமூகம் , டச்சு புற்றுநோய் ,