Abstract
The tooth-marked tongue refers to the tongue with the edge featured in jagged teeth marks, which is a significant indicator for reflecting the conditions of patients' internal organs in Traditional Chinese Medicine (TCM). From the perspective of computer vision, due to the small variance in the global region (original image) but the large variance in the local region (tongue region), especially in the differential region (tongue edge region around landmarks), the recognition of the tooth-marked tongue is a naturally fine-grained classification task. To address this challenging task, a two-stage method based on tongue region detection and tongue landmark detection via deep learning is proposed in this paper. In the first stage, we introduce a cascaded convolutional neural network to detect the tongue region and tongue landmarks simultaneously for minimizing the redundancy information and maximizing discriminative information explicitly. In the second stage, we send not only the detected tongue region but also the detected tongue landmarks to a fine-grained classification network for the final recognition. Conclusively, our method is highly consistent with human perception. Moreover, to the best of our knowledge, we are the first attempt to manage the tooth-marked tongue recognition via deep learning. We conducted extensive experiments with the proposed method. The experimental results demonstrate the effectiveness of the proposed method.
Highlights
As a popular complementary and alternative medicine, traditional Chinese medicine (TCM) is effective in preventing and treating various diseases, which has been incorporated into the latest global medical outline (Ver.2019) by World Health Organization (WHO) [1], [2]
The results of different methods applied in tongue region detection and tongue landmark detection are shown in Table 1, respectively
It could be seen that our deep learning-based method increases by 9.1%/6.3% in Average Precision of 60% (AP60)/Intersection over Union (IoU) compared with the best non-deep learning-based method on the tongue region detection
Summary
As a popular complementary and alternative medicine, traditional Chinese medicine (TCM) is effective in preventing and treating various diseases, which has been incorporated into the latest global medical outline (Ver.2019) by World Health Organization (WHO) [1], [2]. Tongue diagnosis is an effective, inexpensive, and non-invasive method to evaluate the conditions of patients’s internal organs in TCM, which. The popularization of traditional tongue diagnosis has been limited because the diagnosis process relies entirely on the experience and knowledge of the practitioners. Environmental factors (i.e. illumination) and examinee factors (i.e. subjects’ position) may interfere the tongue diagnosis and lead to a unreliable and inconsistent tongue diagnosis result. It is imperative to utilize the image processing and pattern recognition technology in aid of the objective analysis of tongue image.
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