2018英特爾ISEF獲獎作品摘要 機器人與智能機器（人工智能） Intel Finalist Abstract Robotics and Intelligent Machines (AI)

獲獎作品基本信息

年份	2018
學科	機器人與智能機器 Robotics and Intelligent Machines
國家/州	United States of America

獲獎作品名稱

Context Aware Medical Image Super Resolution Using Convolutional Neural Networks

獲獎作品摘要

In recent years, the classical computer vision problem of super-resolution has been approached with deep learning technologies, e.g., convolutional neural networks (CNNs). These new techniques such as SRCNN have vastly surpassed traditional example-based methods such as sparse-coding. High resolution medical images significantly improve the performance of detection, segmentation, and diagnosis of abnormalities. Unfortunately, the quality of medical images is critically dependent on both practical and physical limitations. First, the quality of imaging is directly proportional to the radiative dosage received by the patient. Furthermore, the extended time in cramped machines leaves the patient prone to anxiety, which may result in motion artifacts. Finally, high-powered machines are necessary to produce high-resolution scans, but they are very expensive.?

We propose a novel context-aware CNN architecture, C-SRCNN, as a superior solution to super-resolution, particularly regarding medical imaging. Our novel model employs a multi-channel input into a deep CNN to learn an end-to-end mapping from low-resolution to high-resolution images. Unlike previous techniques, our model is context-aware, having the ability to utilize the surrounding patches of an input image patch for increased performance. The addition of contextual information is apt for medical imaging due to self-similarity between anatomical structures and allows our model to train with more information on a deep and wider network. The model is built using the modern deep learning framework of Tensorflow and Python. Our model has clearly shown superior performance compared to existing work on benchmark datasets as well as on medical images in similar experimental conditions.

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高中生科研 英特爾 Intel ISEF
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高中生科研學術活動 英特爾 Intel ISEF 簡介

英特爾國際科學與工程大獎賽，簡稱 "ISEF"，由美國 Society for Science and the Public（科學和公共服務協會）主辦，英特爾公司冠名贊助，是全球規模最大、等級最高的中學生的科研科創賽事。ISEF 的學術活動學科包括了所有數學、自然科學、工程的全部領域和部分社會科學。ISEF 素有全球青少年科學學術活動的“世界杯”之美譽，旨在鼓勵學生團隊協作，開拓創新，長期專一深入地研究自己感興趣的課題。

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英特爾 ISEF 學術活動詳細介紹

英特爾 ISEF 全程指導方案

· 數學 · 物理 · 化學 · 生物 · 計算機 · 工程 ·

學科簡介：機器人與智能機器 Robotics and Intelligent Machines

Studies in which the use of machine intelligence is paramount to reducing the reliance on human intervention.

Subcategories:

Biomechanics?(BIE):?Studies and apparatus which mimic the role of mechanics in biological systems.

Cognitive Systems?(COG):?Studies/apparatus that operate similarly to the ways humans think and process information. Systems that provide for increased interaction of people and machines to more naturally extend and magnify human expertise, activity, and cognition.

Control Theory?(CON):?Studies that explore the behavior of dynamical systems with inputs, and how their behavior is modified by feedback. ?This includes new theoretical results and the applications of new and established control methods, system modelling, identification and simulation, the analysis and design of control systems (including computer-aided design), and practical implementation.

Machine Learning?(MAC):?Construction and/or study of algorithms that can learn from data.

Robot Kinematics?(KIN):?The study of movement in robotic systems.

Other?(OTH):?Studies that cannot be assigned to one of the above subcategories.?If the project involves multiple subcategories, the principal subcategory should be chosen instead of Other.