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Griffithiana
Journal of film history.
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.
The Chinese Filmography
From A to Z, Abandon Superstitions (1958; Po Chu Mi Xing in Chinese) to Zuo Wenjun and Sima Xiangru (1984; Zuo Wen Jun Ahe Si Ma Xiang Ru), this comprehensive reference work provides filmographic data on 2,444 Chinese features released since the formation of the People's Republic of China. The films reflect the shifting dynamics of the Chinese film industry, from sweeping epics to unabashedly political docudramas, although straight documentaries are excluded from the current work. The entries include the title in English, the Chinese title (in Pinyin romanization with each syllable noted separately for clarity), year of release, studio, technical information (e.g., black and white or color, letterboxed or widescreen), length, technical credits, literary source (when applicable), cast, plot summary, and awards won.
Machine Learning in Medical Imaging
This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully reviewed and selected from 64 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
