人工智能与医学影像融合发展:机遇与挑战附视频

MRI based texture analysis to classify low grade gliomas into astrocytoma and 1p/19q codeleted oligodendroglioma[J] Shun Zhang;Gloria Chia-Yi Chiang;Rajiv S. Magge;Howard Alan Fine;Rohan Ramakrishna;Eileen Wang Chang;Tejas Pulisetty;Yi Wang;Wenzhen Zhu;Ilhami Kovanlikaya Magnetic Resonance Imaging 2019,

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study[J] Sasank Chilamkurthy;Rohit Ghosh;Swetha Tanamala;Mustafa Biviji;Norbert G Campeau;Vasantha Kumar Venugopal;Vidur Mahajan;Pooja Rao;Prashant Warier The Lancet 2018,

Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis[J] Mario Silva;Cornelia M. Schaefer-Prokop;Colin Jacobs;Giovanni Capretti;Francesco Ciompi;Bram van Ginneken;Ugo Pastorino;Nicola Sverzellati Investigative Radiology 2018,

Benchmarking deep learning models on large healthcare datasets[J] Sanjay Purushotham;Chuizheng Meng;Zhengping Che;Yan Liu Journal of Biomedical Informatics 2018,

Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging[J] Ken Chang;Harrison X. Bai;Hao Zhou;Chang Su;Wenya Linda Bi;Ena Agbodza;Vasileios K. Kavouridis;Joeky T. Senders;Alessandro Boaro;Andrew Beers;Biqi Zhang;Alexandra Capellini;Weihua Liao;Qin Shen;Xuejun Li;Bo Xiao;Jane Cryan;Shakti Ramkissoon;Lori Ramkissoon;Keith Ligon;Patrick Y. Wen;Ranjit S. Bindra;John Woo;Omar Arnaout;Elizabeth R. Gerstner;Paul J. Zhang;Bruce R. Rosen;Li

Multiple supervised residual network for osteosarcoma segmentation in CT images[J] Rui Zhang;Lin Huang;Wei Xia;Bo Zhang;Bensheng Qiu;Xin Gao Computerized Medical Imaging and Graphics 2018,

Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18 F-FDG PET/CT images[J] Hongkai Wang;Zongwei Zhou;Yingci Li;Zhonghua Chen;Peiou Lu;Wenzhi Wang;Wanyu Liu;Lijuan Yu EJNMMI Research 2017,

The Effects of Changes in Utilization and Technological Advancements of Cross-Sectional Imaging on Radiologist Workload[J] Robert J. McDonald;Kara M. Schwartz;Laurence J. Eckel;Felix E. Diehn;Christopher H. Hunt;Brian J. Bartholmai;Bradley J. Erickson;David F. Kallmes Academic Radiology 2015,

Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy[J] Marco Ravanelli;Davide Farina;Mauro Morassi;Elisa Roca;Giuseppe Cavalleri;Gianfranco Tassi;Roberto Maroldi European Radiology 2013,

MRI based texture analysis to classify low grade gliomas into astrocytoma and 1p/19q codeleted oligodendroglioma[J] Shun Zhang;Gloria Chia-Yi Chiang;Rajiv S. Magge;Howard Alan Fine;Rohan Ramakrishna;Eileen Wang Chang;Tejas Pulisetty;Yi Wang;Wenzhen Zhu;Ilhami Kovanlikaya Magnetic Resonance Imaging 2019,

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study[J] Sasank Chilamkurthy;Rohit Ghosh;Swetha Tanamala;Mustafa Biviji;Norbert G Campeau;Vasantha Kumar Venugopal;Vidur Mahajan;Pooja Rao;Prashant Warier The Lancet 2018,

Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis[J] Mario Silva;Cornelia M. Schaefer-Prokop;Colin Jacobs;Giovanni Capretti;Francesco Ciompi;Bram van Ginneken;Ugo Pastorino;Nicola Sverzellati Investigative Radiology 2018,

Benchmarking deep learning models on large healthcare datasets[J] Sanjay Purushotham;Chuizheng Meng;Zhengping Che;Yan Liu Journal of Biomedical Informatics 2018,

Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging[J] Ken Chang;Harrison X. Bai;Hao Zhou;Chang Su;Wenya Linda Bi;Ena Agbodza;Vasileios K. Kavouridis;Joeky T. Senders;Alessandro Boaro;Andrew Beers;Biqi Zhang;Alexandra Capellini;Weihua Liao;Qin Shen;Xuejun Li;Bo Xiao;Jane Cryan;Shakti Ramkissoon;Lori Ramkissoon;Keith Ligon;Patrick Y. Wen;Ranjit S. Bindra;John Woo;Omar Arnaout;Elizabeth R. Gerstner;Paul J. Zhang;Bruce R. Rosen;Li

Multiple supervised residual network for osteosarcoma segmentation in CT images[J] Rui Zhang;Lin Huang;Wei Xia;Bo Zhang;Bensheng Qiu;Xin Gao Computerized Medical Imaging and Graphics 2018,

Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18 F-FDG PET/CT images[J] Hongkai Wang;Zongwei Zhou;Yingci Li;Zhonghua Chen;Peiou Lu;Wenzhi Wang;Wanyu Liu;Lijuan Yu EJNMMI Research 2017,

The Effects of Changes in Utilization and Technological Advancements of Cross-Sectional Imaging on Radiologist Workload[J] Robert J. McDonald;Kara M. Schwartz;Laurence J. Eckel;Felix E. Diehn;Christopher H. Hunt;Brian J. Bartholmai;Bradley J. Erickson;David F. Kallmes Academic Radiology 2015,

Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy[J] Marco Ravanelli;Davide Farina;Mauro Morassi;Elisa Roca;Giuseppe Cavalleri;Gianfranco Tassi;Roberto Maroldi European Radiology 2013,