Resources: Page 229

AI assesses cardiovascular risk on routine chest CT
By Erik L. Ridley
Tuesday, November 28 | 11:40 a.m.-11:50 a.m. | SSG13-08 | Room S404ABA Dutch team has found that its artificial intelligence (AI) algorithm can automatically perform cardiovascular risk assessment from routine chest CT studies.
November 5, 2017
CAD enables lower radiation dose in CT lung screening
By Abraham Kim
Tuesday, November 28 | 11:20 a.m.-11:30 a.m. | SSG13-06 | Room S404ABIn this talk, researchers will describe how computer-aided detection (CAD) can lead to marked reductions in radiation dose on low-dose CT lung cancer screening scans, even when image slice thickness is altered.
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
More may not always be better in deep learning
By Erik L. Ridley
Tuesday, November 28 | 11:00 a.m.-11:10 a.m. | SSG13-04 | Room S404ABHaving more layers in a convolutional neural network doesn't necessarily lead to better performance for medical imaging tasks, reports a group from Chicago.
November 5, 2017
Deep learning yields real-time coronary calcium scoring
By Erik L. Ridley
Tuesday, November 28 | 10:50 a.m.-11:00 a.m. | SSG13-03 | Room S404ABA deep-learning algorithm can swiftly quantify coronary artery calcium scores on low-dose CT lung screening exams, according to researchers from the Netherlands.
November 5, 2017
Algorithm detects, segments lung nodules on CT
By Erik L. Ridley
Tuesday, November 28 | 10:40 a.m.-10:50 a.m. | SSG13-02 | Room S404ABIn this scientific session, a team from imaging software developer Arterys will present its deep learning-based approach to detecting and segmenting lung nodules on CT scans.
November 5, 2017
Deep learning helps forecast cancer treatment response
By Erik L. Ridley
Tuesday, November 28 | 10:30 a.m.-10:40 a.m. | SSG13-01 | Room S404ABThe combination of deep learning and radiomics features could help radiologists estimate the likelihood of a bladder cancer patient responding to neoadjuvant chemotherapy.
November 5, 2017
Machine learning helps predict lithotripsy outcome
By Erik L. Ridley
Monday, November 27 | 3:50 p.m.-4:00 p.m. | SSE12-06 | Room E353AA Swiss group will present its experience in using CT texture analysis and machine learning to predict the successful treatment of kidney stones with shock-wave lithotripsy.
November 5, 2017
AI can detect, characterize kidney stones
By Erik L. Ridley
Monday, November 27 | 3:40 p.m.-3:50 p.m. | SSE12-05 | Room E353AAn artificial intelligence (AI) algorithm can be used to accurately detect and characterize kidney stones, according to researchers from Boston.
November 5, 2017
Machine learning can help diagnose Crohn's disease
By Erik L. Ridley
Monday, November 27 | 11:50 a.m.-12:00 p.m. | SSC05-09 | Room E451AA machine-learning technique can diagnose Crohn's disease with high sensitivity and specificity, researchers from Italy report.
November 5, 2017
AI exploits tumor imaging features to predict survival
By Erik L. Ridley
Monday, November 27 | 11:50 a.m.-12:00 p.m. | SSC04-09 | Room E353AArtificial intelligence (AI) can make use of tumor heterogeneity features on MRI to accurately predict the survival of metastatic colon cancer patients, according to a study by Harvard researchers.
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
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