2017英特尔ISEF获奖作品摘要 机器人与智能机器（人工智能） Intel Finalist Abstract Robotics and Intelligent Machines (AI)

获奖作品基本信息

年份	2017
学科	机器人与智能机器 Robotics and Intelligent Machines
国家/州	United States of America

获奖作品名称

Mitosis Detection and Tumor Grading Using Deep Convolutional Neural Networks

获奖作品摘要

Analyzing mitosis proliferation is crucial to physician grading of tumor severity and prognosis. Despite the time and effort poured into automated mitosis detection, no systems have been able to perform at the level of skilled pathologists, who manually examine slide images for mitotic cells.

Deep learning is an emerging field of machine learning based on modeling high-level abstractions using large interconnected networks of neurons. We build a custom deep convolutional network architecture, based on the seminal GoogleNet model and principles of aggressive, multiscale data augmentation. Since mitoses are extremely rare compared to normal cells, we also develop a novel multi-stage “bootstrapping” algorithm to extract meaningful training examples from highly imbalanced data. Our deep convolutional neural network achieves an F1 score of 0.85 on the 717-image TUPAC dataset. This trained model also generalizes well, surpassing the best F1-scores obtained in previous mitosis competitions.

We then develop a pipeline to grade whole slide images using an intuitive ROI selection algorithm and the trained mitosis detector. Our algorithms detect crucial regions within enormous whole slide images and use these regions to extrapolate levels of tumor-linked mitotic activity. The genes identified by our continuous mitosis scores outperform pathologist scores in their association to cancer and cell cycle functions/ pathways. Finally, we build a gene-level model to predict the mitosis scores from RNA- sequence data. From this model, we extract 10 gene predictions possibly linked to tumor mitotic activity.

We hope our research is a step towards a future where physicians use precise, deep- learning- enabled analyses of mitotic activity to diagnose and treat patients.

高中生科研学术活动 英特尔 Intel ISEF 简介

英特尔国际科学与工程大奖赛，简称 "ISEF"，由美国 Society for Science and the Public（科学和公共服务协会）主办，英特尔公司冠名赞助，是全球规模最大、等级最高的中学生的科研科创赛事。ISEF 的学术活动学科包括了所有数学、自然科学、工程的全部领域和部分社会科学。ISEF 素有全球青少年科学学术活动的“世界杯”之美誉，旨在鼓励学生团队协作，开拓创新，长期专一深入地研究自己感兴趣的课题。

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英特尔 ISEF 学术活动详细介绍

英特尔 ISEF 全程指导方案

· 数学 · 物理 · 化学 · 生物 · 计算机 · 工程 ·

学科简介：机器人与智能机器 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.