Automated characterization of different vessel wall tissues including atherosclerotic plaques, branchings and stents from intravascular ultrasound (IVUS) gray-scale images was addressed. The texture features of each frame were firstly detected with local binary pattern (LBP), Haar-like and Gabor filter in the present study. Then, a Gentle Adaboost classifier was designed to classify tissue features. The methods were validated with clinically acquired image data. The manual characterization results obtained by experienced physicians were adopted as the golden standard to evaluate the accuracy. Results indicated that the recognition accuracy of lipidic plaques reached 94.54%, while classification precision of fibrous and calcified plaques reached 93.08%. High recognition accuracy can be reached up to branchings 93.20% and stents 93.50%, respectively.
For tooth segmentation problem on the three-dimensional computed tomography (CT) volume data, this paper proposes a regional adaptive deformable model for tooth structure measurement of CT images. The proposed method combines the automatic thresholding segmentation, CV active contour model, and graph-cut. Firstly, we achieved the segmentation and location of dental crowns by automatic thresholding segmentation. And then by using the above segmentation result as the initial contour, we utilized active contour method to slice gradually the segment of remaining tooth. By incorporating active contour and graph-cut then, we realized the accurate segmentation for tooth root, which is the most difficult to be segmented. The experimental results showed that the proposed tooth structure measurement accurately and automatically segmented dental crowns from CT data, and then rapidly and accurately segmented the tooth neck and tooth root. The structure of tooth could be effectively segmented from CT data by using the proposed method. Experimental results indicated that the proposed method was rather robust and accurate, and could effectively assist the doctor for diagnosis in clinical treatment.
Objective To evaluate the safety and efficacy of treating type Ⅱ endoleaks after endovascular aneurysm repair (EVAR) of abdominal aortic aneurysms with coil embolization. Methods A retrospective review of patients with type Ⅱ endoleaks treated with coil embolization was performed. Data regarding the technical, clinical, and imaging outcomes during perioperation and followed-up were collected. Results The technical success rate and the initial clinical success rate of treating type Ⅱ endoleaks with coil embolization were 100% (14/14). The mean operating time was (124.3±11) min, a mean of (127±15) mL contrast agent and a mean of (7±2) coils were used. During perioperation, one patient suffered left limb paralysis, all the patients were discharged with no perioperative mortality. Twelve patients were followed-up. During the period of 3 to 57 months of followed-up (average: 17.3 months), Type Ⅱ endoleaks reoccurred in one patient with coil embolization of the feeding vessels alone and two patients with coil embolization of the aneurysm sac alone. Since the aneurysms did not enlarge during the followed-up, these 3 patients continued followed-up without reinterventions. Conclusion Treating type Ⅱ endoleaks with coil embolization appears to be safe, and it can prevent aneurysm sac enlargement effectively. Because of the high risk of reoccurrence, follow-up after embolization is important.