Breast: Page 160

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 5, 2017
Deep learning with breast MRI boosts 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 5, 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 5, 2017
Volpara wins 25 VolparaEnterprise installations
By AuntMinnie.com staff writers
Breast imaging software developer Volpara Solutions has announced the first 25 sales and installations of its VolparaEnterprise software.
November 2, 2017
Hologic adds Dutch mammo supply deal
By AuntMinnie.com staff writers
Women's imaging firm Hologic and its Netherlands' distributor Tromp Medical will supply mammography systems for the Dutch Breast Cancer Screening Program.
November 1, 2017
Surveillance OK for certain type of breast lesion
By AuntMinnie.com staff writers
Surveillance is safe for a particular type of noncancerous breast lesion that is typically treated surgically, according to a study published online October 31 in the Journal of the American College of Surgeons.
October 31, 2017
Breast MRI neural networks predict recurrence scores
By Kate Madden Yee
Friday, December 1 | 11:20 a.m.-11:30 a.m. | SST01-06 | Room E450BResearchers in New York have found that deep-learning networks can be trained with breast MRI data to predict Oncotype DX recurrence scores.
October 31, 2017
Texture analysis helps differentiate breast abnormalities
By Wayne Forrest
Thursday, November 30 | 11:50 a.m.-12:00 p.m. | SSQ01-09 | Room E450AJapanese researchers plan to extol the diagnostic performance of texture analysis with dynamic contrast-enhanced breast MRI for nonmass enhancement and the differentiation of malignant and benign lesions.
October 31, 2017
Deep learning with breast MRI boosts 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.
October 31, 2017
Breast MRI performs well across many risk factors
By Kate Madden Yee
Tuesday, November 28 | 8:50 a.m.-9:00 a.m. | RC315-02 | Arie Crown TheaterScreening breast MRI is an effective tool for women who carry the BRCA mutation and also for those with a history of breast cancer and/or high-risk lesions, according to research being presented Tuesday morning.
October 31, 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.
October 31, 2017
Texture analysis helps differentiate breast abnormalities
By Wayne Forrest
Thursday, November 30 | 11:50 a.m.-12:00 p.m. | SSQ01-09 | Room E450AJapanese researchers plan to extol the diagnostic performance of texture analysis with dynamic contrast-enhanced breast MRI for nonmass enhancement and the differentiation of malignant and benign lesions.
October 30, 2017
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