Delineation of ischemic lesion from brain MRI using attention gated fully convolutional network
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ORIGINAL ARTICLE
Delineation of ischemic lesion from brain MRI using attention gated fully convolutional network R. Karthik1 · Menaka Radhakrishnan1 · R. Rajalakshmi2 · Joel Raymann2 Received: 2 July 2020 / Revised: 16 October 2020 / Accepted: 24 October 2020 © Korean Society of Medical and Biological Engineering 2020
Abstract Precise delineation of the ischemic lesion from unimodal Magnetic Resonance Imaging (MRI) is a challenging task due to the subtle intensity difference between the lesion and normal tissues. Hence, multispectral MRI modalities are used for characterizing the properties of brain tissues. Traditional lesion detection methods rely on extracting significant hand-engineered features to differentiate normal and abnormal brain tissues. But the identification of those discriminating features is quite complex, as the degree of differentiation varies according to each modality. This can be addressed well by Convolutional Neural Networks (CNN) which supports automatic feature extraction. It is capable of learning the global features from images effectively for image classification. But it loses the context of local information among the pixels that need to be retained for segmentation. Also, it must provide more emphasis on the features of the lesion region for precise reconstruction. The major contribution of this work is the integration of attention mechanism with a Fully Convolutional Network (FCN) to segment ischemic lesion. This attention model is applied to learn and concentrate only on salient features of the lesion region by suppressing the details of other regions. Hence the proposed FCN with attention mechanism was able to segment ischemic lesion of varying size and shape. To study the effectiveness of attention mechanism, various experiments were carried out on ISLES 2015 dataset and a mean dice coefficient of 0.7535 was obtained. Experimental results indicate that there is an improvement of 5% compared to the existing works. Keywords Deep neural network · FCN · Attention · Ischemic lesion segmentation · MRI
1 Introduction Ischemic stroke arises due to the accumulation of fatty deposits in the blood vessels of the brain. When the fatty particles accumulate at one spot, it affects the flow of blood and vital nutrients. This eventually leads to cell death in the occluded area. The primary treatment option in acute * Menaka Radhakrishnan [email protected] R. Karthik [email protected] R. Rajalakshmi [email protected] Joel Raymann [email protected] 1
Centre for Cyber Physical Systems, Vellore Institute of Technology, Chennai, India
School of Computing Sciences and Engineering, Vellore Institute of Technology, Chennai, Chennai, India
2
ischemic stroke concentrates on dealing with this occlusion quickly with the help of thrombolysis. This thrombolytic process will be safe and effective only if it is initiated within 3 to 4.5 h of symptom onset [1]. Neuroimaging techniques prove to be a gold standard in identifying the actual cause of infarction. The infarction can be eith
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