Cone-beam computed tomography (CBCT) is widely used in dentistry, surgery, radiotherapy and other medical fields. However, repeated CBCT scans expose patients to additional radiation doses, increasing the risk of secondary malignant tumors. Low-dose CBCT image reconstruction technology, which employs advanced algorithms to reduce radiation dose while enhancing image quality, has emerged as a focal point of recent research. This review systematically examined deep learning-based methods for low-dose CBCT reconstruction. It compared different network architectures in terms of noise reduction, artifact removal, detail preservation, and computational efficiency, covering three approaches: image-domain, projection-domain, and dual-domain techniques. The review also explored how emerging technologies like multimodal fusion and self-supervised learning could enhance these methods. By summarizing the strengths and weaknesses of current approaches, this work provides insights to optimize low-dose CBCT algorithms and support their clinical adoption.
Cone-Beam Computed Tomography/methods* ; Deep Learning ; Humans ; Algorithms ; Image Processing, Computer-Assisted/methods* ; Radiation Dosage ; Artifacts

Objective:To evaluate the anxiety and depression symptoms of burning mouth syndrome (BMS), and to explore risk factors to BMS.Method:In this case-control study,147 patients with BMS and 140 sex-and age-matched healthy volunteers were recruited.Three questionnaires were used to collect information of psychical and mental condition.The Self-Rating Anxiety Scale (SAS)and Self-Rating Depression Scale (SDS)were applied to evaluate symptoms of anxiety and depression.The scores of SAS and SDS were statistically analyzed by t-test.The risk factors of BMS were statistically analyzed by Chi-square test and logistic regression analysis.Result:The scores of SAS and SDS were higher in the patients with BMS than in the controls [SAS:(44.4 ±9.9)vs. (35.7 ±6.2);SDS:(48.1 ±11.6)vs.(37.5 ±8.9)].The risk factors of BMS included ischemic stroke (OR =4.46,95%CI:1.87 -10.95),low level of education (OR =1.91,95%CI:1.04 -3.49),anxiety symptom (OR =8.12,95%CI:2.60 -25.37)and depression symptom (OR =2.57,95%CI:1.26 -5.27).Conclusion:BMS is a multi-factorial disease.It indicates that ischemic stroke,lower level of education,anxiety symptom and depression symptom are the risk factors of BMS.A positive association could be established between psychological alterations and BMS.According to these findings it can be assumed that mental factors should be taking into account in the etiologyof BMS.It should be advocated to treat BMS patients by psychotherapy.