Dataset Information

Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally.

ABSTRACT: Intense interest in applying convolutional neural networks (CNNs) in biomedical image analysis is wide spread, but its success is impeded by the lack of large annotated datasets in biomedical imaging. Annotating biomedical images is not only tedious and time consuming, but also demanding of costly, specialty-oriented knowledge and skills, which are not easily accessible. To dramatically reduce annotation cost, this paper presents a novel method called AIFT (active, incremental fine-tuning) to naturally integrate active learning and transfer learning into a single framework. AIFT starts directly with a pre-trained CNN to seek "worthy" samples from the unannotated for annotation, and the (fine-tuned) CNN is further fine-tuned continuously by incorporating newly annotated samples in each iteration to enhance the CNN's performance incrementally. We have evaluated our method in three different biomedical imaging applications, demonstrating that the cost of annotation can be cut by at least half. This performance is attributed to the several advantages derived from the advanced active and incremental capability of our AIFT method.

SUBMITTER: Zhou Z

PROVIDER: S-EPMC6191179 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Publications

Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally.

Zhou Zongwei Z Shin Jae J Zhang Lei L Gurudu Suryakanth S Gotway Michael M Liang Jianming J

Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition 20170701

Intense interest in applying convolutional neural networks (CNNs) in biomedical image analysis is wide spread, but its success is impeded by the lack of large annotated datasets in biomedical imaging. Annotating biomedical images is not only tedious and time consuming, but also demanding of costly, specialty-oriented knowledge and skills, which are not easily accessible. To dramatically reduce annotation cost, this paper presents a novel method called AIFT (active, incremental fine-tuning) to na ...[more]

PMID: 30337799

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Dataset Information

Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally.

Publications

Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally.

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