Objective To analyze reasons of postoperat iv e relapse of inguinal hernia and to explore the clinical significance of laparos copic transabdominal preperitoneal (TAPP) repair for recurrent hernia. Methods We retrospectively analyzed clinical data of 24 cases of recurr ent inguinal hernia treated by laparoscopic TAPP repair from June 1998 to Octobe r 2003 in this hospital. There were 11 cases of direct hernia and 13 cases of in direct hernia. Results Operations were completed successfully in all the 24 cases without conversions to open surgery. The operation time was 47~128 min (mean, 69 min), and the postoperative hospital stay, 2~5 days (mean, 3 days). Urinary retention happened in 6 cases after the operation, in which a F oley urethral catheter was indwelled for 1~3 days. There were no complications s uch as wound infection, scrotal hematoma or pneumatosis. Follow-up checkups were made for 2~66 months (mean, 27 months) in all the 24 cases. No recurrence was o bserved. Conclusions Laparoscopic TAPP repair for recurrent in guinal hernia has advantages of minimal invasion and few complications, being a safe and feasible option for treating recurrent inguinal hernia.

We presented a new method for vessel segmentation and vascular structure recognition for coronary angiographic images. During vessel segmentation, a new vessel function was proposed to attain vessel feature map. Then the region growing algorithm was implemented with an automatic selection of seed point, extraction of main vessel branch, and vessel detail repairing. In the algorithm of vascular structure recognition, a fuzzy operator was used, which can detect the structures of vascular segments, bifurcations, crosses, and tips. The experimental results indicated that there was about 5 percent larger vessel region which was extracted by the proposed segmentation method than that by the simple region growing algorithm, and several thinner vessels were resumed from the lower gray region. The results also indicated that the fuzzy operator could correctly infer the simulative and real vessel structure with 100% and 90.59% correctness rate on the average, respectively.
Algorithms ; Coronary Angiography ; Humans ; Radiographic Image Enhancement ; methods ; X-Rays