Radiation Oncology/Therapy: Page 118

AI may enhance MRI-guided adaptive radiation therapy
By Erik L. Ridley
Wednesday, November 29 | 3:00 p.m.-3:10 p.m. | SSM12-01 | Room S404CDArtificial intelligence (AI) can provide automatic contouring of tumors and organs to support daily MRI-guided adaptive radiation therapy, researchers will report in this Wednesday session.
November 5, 2017
CAD software tracks changes in brain metastases
By Erik L. Ridley
Wednesday, November 29 | 11:00 a.m.-11:10 a.m. | RC505-09 | Room E451BComputer-aided detection (CAD) software can be used to detect and quantify changes in brain metastases on MRI, according to researchers from Philadelphia.
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
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
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
Deep learning helps find lung nodules on chest x-ray
By Erik L. Ridley
Monday, November 27 | 11:00 a.m.-11:10 a.m. | SSC03-04 | Room S504CDA U.K. team has found that deep learning-powered computer-aided detection software could potentially act as a second reader for chest radiographs.
November 5, 2017
Deep learning can assess malignancy risk of lung nodules
By Erik L. Ridley
Sunday, November 26 | 10:55 a.m.-11:05 a.m. | SSA12-02 | Room S403AIn this scientific session, researchers will describe how a deep-learning algorithm can provide an objective measure for assessing the malignancy risk of a lung nodule.
November 5, 2017
AI can predict invasiveness of lung adenocarcinoma
By Erik L. Ridley
Sunday, November 26 | 10:45 a.m.-10:55 a.m. | SSA05-01 | Room S404CDA Japanese group has found that an artificial intelligence (AI) algorithm can predict the level of pathological invasiveness of lung adenocarcinoma nearly as accurately as a highly experienced radiologist.
November 5, 2017
Dual-energy CT analysis predicts metastasis of neck SCC
By Abraham Kim
Tuesday, November 28 | 11:20 a.m.-11:30 a.m. | SSG11-06 | Room N229In this study, Canadian researchers investigated the potential of analyzing dual-energy CT scans to determine the nodal status of squamous cell carcinoma (SCC) in the head and neck.
November 1, 2017
Can CT differentiate low- from high-grade renal tumors?
By Abraham Kim
Monday, November 27 | 11:20 a.m.-11:30 a.m. | SSC06-06 | Room N230BRadiologists can combine subjective and quantitative analyses of CT scans to help them grade chromophobe renal cell carcinomas, Canadian researchers will report in this Monday morning presentation.
November 1, 2017
CT temporal subtraction helps detect spinal bone metastases
By Abraham Kim
Sunday, November 26 | 12:05 p.m.-12:15 p.m. | SSA15-09 | Room S406BIntegrating a temporal subtraction technique into CT scans improves the detection of sclerotic bone metastases in the spine, according to researchers from Japan.
November 1, 2017
Ferumoxytol-enhanced MRI could benefit glioma patients
By Wayne Forrest
Sunday, November 26 | 11:35 a.m.-11:45 a.m. | SSA17-06 | Room N228Researchers from Stanford University plan to provide additional evidence on the potential for ferumoxytol-enhanced MRI to detect and quantify macrophages in high-grade gliomas.
October 31, 2017
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