Breast: Page 164

AI-based software could reduce unnecessary biopsies
By Wayne Forrest
Wednesday, November 29 | 11:20 a.m.-11:30 a.m. | SSK01-06 | Room E450AA group from the University of Southern California will discuss the performance of a quantitative computer-aided detection software application that uses deep learning and artificial intelligence (AI) to improve mammography screening.
November 8, 2017
Novel deep-learning process aids breast cancer detection
By Wayne Forrest
Wednesday, November 29 | 11:10 a.m.-11:20 a.m. | SSK02-05 | Room E451AIn this talk, researchers will present a method of combining routine clinical data and natural language processing to create large datasets for deep learning and enhancing breast cancer diagnosis.
November 8, 2017
Deep-learning CAD adds to breast ultrasound findings
By Wayne Forrest
Wednesday, November 29 | 10:50 a.m.-11:00 a.m. | SSK02-03 | Room E451AThe potential benefits of deep-learning computer-aided detection (CAD) for breast ultrasound will be outlined in this Wednesday morning presentation by researchers from South Korea.
November 8, 2017
Deep learning could lend a hand with digital mammo
By Wayne Forrest
Wednesday, November 29 | 10:40 a.m.-10:50 a.m. | SSK02-02 | Room E451AA computer system based on deep-learning technology was as efficient as radiologists in detecting breast cancer on digital mammography exams in a study by a group from Sweden and the Netherlands.
November 8, 2017
Deep-learning software improves breast US performance
By Kate Madden Yee
Tuesday, November 28 | 3:40 p.m.-3:50 p.m. | SSJ02-05 | Room E450AWhen it comes to identifying breast cancer, deep-learning software for breast ultrasound achieves diagnostic accuracy comparable to that of radiologists, Swiss researchers have found.
November 8, 2017
CAD boosts performance of contrast spectral mammography
By Kate Madden Yee
Tuesday, November 28 | 12:15 p.m.-12:45 p.m. | BR234-SD-TUA2 | Lakeside, BR Community, Station 2Computer-aided diagnosis of contrast-enhanced spectral mammography (CAD-CESM) can help reduce false positives, according to this Tuesday afternoon poster presentation.
November 8, 2017
Deep learning improves mammography multitasking
By Wayne Forrest
Tuesday, November 28 | 11:30 a.m.-11:40 a.m. | SSG13-07 | Room S404ABEveryone can use some help when multitasking. Researchers from the University of Michigan will present the benefits to mammography from a deep convolutional neural network based on a multitask transfer learning algorithm.
November 8, 2017
Deep learning with breast MRI helps with lesion detection
By Kate Madden Yee
Tuesday, November 28 | 11:20 a.m.-11:30 a.m. | RC315-14 | Arie Crown TheaterA deep-learning method using multiparametric breast MRI improves automated detection and characterization of breast lesions, according to research being presented at this Tuesday morning session.
November 8, 2017
Breast MRI neural network predicts treatment response
By Kate Madden Yee
Monday, November 27 | 11:50 a.m.-12:00 p.m. | RC215-17 | Arie Crown TheaterIn this session, researchers will discuss how neural networks based on a breast MRI tumor dataset can help clinicians predict patient response to neoadjuvant chemotherapy.
November 8, 2017
IMV: Imaging sites happiest with mammo systems
By AuntMinnie.com staff writers
Medical imaging facilities are most satisfied with the performance of their mammography systems, according to the results of a customer satisfaction survey performed by market research firm IMV Medical Information Division. Meanwhile, CT scored the highest in terms of OEM service satisfaction.
November 6, 2017
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Deep-learning software boosts breast US performance
By Kate Madden Yee
Tuesday, November 28 | 3:40 p.m.-3:50 p.m. | SSJ02-05 | Room E450AWhen it comes to identifying breast cancer, deep-learning software for breast ultrasound achieves diagnostic accuracy comparable to that of radiologists, Swiss researchers have found.
November 6, 2017
CEUS can reduce breast biopsy rates
By Kate Madden Yee
Tuesday, November 28 | 3:00 p.m.-3:10 p.m. | SSJ02-01 | Room E450AIn this session, researchers will discuss how using contrast-enhanced ultrasound (CEUS) to evaluate BI-RADS 4 or 5 breast lesions can reduce biopsy rates and increase cancer-to-biopsy yield.
November 6, 2017
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