The bi-elliptical deformable contour and its application to automated tongue segmentation in Chinese medicine

2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Advances in automated tongue diagnosis techniques

This paper reviews the recent advances in a significant constituent of traditional oriental medicinal technology, called tongue diagnosis. Tongue diagnosis can be an effective, noninvasive method to perform an auxiliary diagnosis any time anywhere, which can support the global need in the primary healthcare system. This work explores the literature to evaluate the works done on the various aspects of computerized tongue diagnosis, namely preprocessing, tongue detection, segmentation, feature extraction, tongue analysis, especially in traditional Chinese medicine (TCM). In spite of huge volume of work done on automatic tongue diagnosis (ATD), there is a lack of adequate survey, especially to combine it with the current diagnosis trends. This paper studies the merits, capabilities, and associated research gaps in current works on ATD systems. After exploring the algorithms used in tongue diagnosis, the current trend and global requirements in health domain motivates us to propose a conceptual framework for the automated tongue diagnostic system on mobile enabled platform. This framework will be able to connect tongue diagnosis with the future point-of-care health system

TongueSAM: An Universal Tongue Segmentation Model Based on SAM with Zero-Shot

Tongue segmentation serves as the primary step in automated TCM tongue diagnosis, which plays a significant role in the diagnostic results. Currently, numerous deep learning based methods have achieved promising results. However, most of these methods exhibit mediocre performance on tongues different from the training set. To address this issue, this paper proposes a universal tongue segmentation model named TongueSAM based on SAM (Segment Anything Model). SAM is a large-scale pretrained interactive segmentation model known for its powerful zero-shot generalization capability. Applying SAM to tongue segmentation enables the segmentation of various types of tongue images with zero-shot. In this study, a Prompt Generator based on object detection is integrated into SAM to enable an end-to-end automated tongue segmentation method. Experiments demonstrate that TongueSAM achieves exceptional performance across various of tongue segmentation datasets, particularly under zero-shot. TongueSAM can be directly applied to other datasets without fine-tuning. As far as we know, this is the first application of large-scale pretrained model for tongue segmentation. The project and pretrained model of TongueSAM be publiced in :https://github.com/cshan-github/TongueSAM

Differences in the Tongue Features of Primary Dysmenorrhea Patients and Controls over a Normal Menstrual Cycle

Background. The aims of this study were to investigate the relationships between tongue features and the existence of menstrual pain and to provide basic information regarding the changes in tongue features during a menstrual cycle. Methods. This study was conducted at the Kyung Hee University Medical Center. Forty-eight eligible participants aged 20 to 29 years were enrolled and assigned to two groups according to their visual analogue scale (VAS) scores. Group A included 24 females suffering from primary dysmenorrhea (PD) caused by qi stagnation and blood stasis syndrome with VAS ≥ 4. In contrast, Group B included 24 females with few premenstrual symptoms and VAS < 4. All participants completed four visits (menses-follicular-luteal-menses phases), and the tongue images were taken by using a computerized tongue image analysis system (CTIS). Results. The results revealed that the tongue coating color value and the tongue coating thickness in the PD group during the menstrual phase were significantly lower than those of the control group (P=0.031 and P=0.029, resp.). Conclusions. These results suggest that the tongue features obtained from the CTIS may serve as a supplementary means for the differentiation of syndromes and the evaluation of therapeutic effect and prognosis in PD. Trial Registration. This trial was registered with Clinical Research Information Service, registration number KCT0001604, registered on 27 August 2015

Fast marching over the 2D Gabor magnitude domain for tongue body segmentation

Author name used in this publication: David ZhangVersion of RecordPublishe