第3回計算解剖学セミナー

開催概要

プログラム

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  • 講師
    • 鈴木 賢治 先生 (シカゴ大学 助教授)
  • 講演タイトル
    • お手本から“学ぶ”医用画像認識 (Machine-Learning Approach to Medical Pattern Recognition)
  • 講演概要
    • Machine leaning plays an essential role in medical pattern recognition, because objects in medical images such as lesions and anatomic structures cannot be represented by simple equations accurately; thus, tasks in medical pattern recognition require “learning from examples” essentially. We have been studying on machine-learning methods called massive-training artificial neural networks (MTANNs) for various tasks in medical pattern recognition. An MTANN is a supervised pixel/voxel-based machine-learning technique for medical image processing and pattern recognition. The MTANN directly learns the relationship between “teaching” input and its desired images to enhance specific patterns and suppresses other patterns in medical images. An MTANN is a versatile tool; and thus, it is applicable to various tasks in medical pattern recognition, such as enhancing edges traced by physicians, lesion enhancement on CT images, lung nodule detection on thoracic CT images and chest radiographs, distinction between benign and malignant nodules on CT images, separation of ribs from soft tissue in chest radiographs, and polyp detection in CT colonography

問い合わせ先

  • 佐藤 嘉伸 (大阪大学 大学院医学系研究科 放射線医学教室 准教授)

共催

当日の様子

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Last-modified: 2013-09-03 (Tue) 11:24:15 (1508d)