AIM: To improve the diagnostic accuracy in patients with symptoms and signs of appendicitis, but without confirmative computed tomography (CT) findings.
AIM:To identify risk factors of actual appendiceal perforation when computed tomography(CT)scans suggest nonperforated appendicitis and accordingly determine surgical priority.METHODS:We collected database of 1362 pat...AIM:To identify risk factors of actual appendiceal perforation when computed tomography(CT)scans suggest nonperforated appendicitis and accordingly determine surgical priority.METHODS:We collected database of 1362 patients who underwent an appendectomy for acute appendicitis between 2006 and 2013.A single radiologist selected1236 patients whose CT scans were suggestive ofnonperforated appendicitis.Patients were divided into 2 groups:actual nonperforation group and actual perforation group according to intraoperative and pathologic features.Comparison of the 2 groups were made using binary logistic regression.RESULTS:Of 1236 patients,90(7.3%)were found to have actual appendiceal perforation.Four risk factors related with actual appendiceal perforation were identified:body temperature≥37.6℃(HR=1.912,95%CI:1.161-3.149;P=0.011),out-ofhospital symptom duration≥72 h(HR=2.454,95%CI:1.292-4.662;P=0.006),age≥35 years(HR=3.358,95%CI:1.968-5.728;P<0.001),and appendiceal diameter on CT scan≥8 mm(HR=4.294,95%CI:1.034-17.832;P=0.045).Actual appendiceal perforation group showed longer operation time,later initiation of diet,longer use of parenteral narcotics,longer hospital stay,and higher incidence of postoperative complications(P<0.05).CONCLUSION:We proposed here new criteria to select patients with adverse clinical outcomes after appendectomy among the patients with radiologically nonperforated appendicitis.Surgical appendectomy outcomes could be improved by determining the surgical priority according to our criteria.展开更多
Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the sa...Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the same person within one image,but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same.When tracking the same object using two or more images,there must be a way to determine that objects existing in different images are the same object.Therefore,this paper attempts to determine the same object present in different images using color information among the unique information of the object.Thus,this study proposes a multiple-object-tracking method using histogram stamp extraction in closed-circuit television applications.The proposed method determines the presence or absence of a target object in an image by comparing the similarity between the image containing the target object and other images.To this end,a unique color value of the target object is extracted based on its color distribution in the image using three methods:mean,mode,and interquartile range.The Top-N accuracy method is used to analyze the accuracy of each method,and the results show that the mean method had an accuracy of 93.5%(Top-2).Furthermore,the positive prediction value experimental results show that the accuracy of the mean method was 65.7%.As a result of the analysis,it is possible to detect and track the same object present in different images using the unique color of the object.Through the results,it is possible to track the same object that can minimize manpower without using personal information when detecting objects in different images.In the last response speed experiment,it was shown that when the mean was used,the color extraction of the object was possible in real time with 0.016954 s.Through this,it is possible to detect and track the same object in real time when using the proposed method.展开更多
文摘AIM: To improve the diagnostic accuracy in patients with symptoms and signs of appendicitis, but without confirmative computed tomography (CT) findings.
文摘AIM:To identify risk factors of actual appendiceal perforation when computed tomography(CT)scans suggest nonperforated appendicitis and accordingly determine surgical priority.METHODS:We collected database of 1362 patients who underwent an appendectomy for acute appendicitis between 2006 and 2013.A single radiologist selected1236 patients whose CT scans were suggestive ofnonperforated appendicitis.Patients were divided into 2 groups:actual nonperforation group and actual perforation group according to intraoperative and pathologic features.Comparison of the 2 groups were made using binary logistic regression.RESULTS:Of 1236 patients,90(7.3%)were found to have actual appendiceal perforation.Four risk factors related with actual appendiceal perforation were identified:body temperature≥37.6℃(HR=1.912,95%CI:1.161-3.149;P=0.011),out-ofhospital symptom duration≥72 h(HR=2.454,95%CI:1.292-4.662;P=0.006),age≥35 years(HR=3.358,95%CI:1.968-5.728;P<0.001),and appendiceal diameter on CT scan≥8 mm(HR=4.294,95%CI:1.034-17.832;P=0.045).Actual appendiceal perforation group showed longer operation time,later initiation of diet,longer use of parenteral narcotics,longer hospital stay,and higher incidence of postoperative complications(P<0.05).CONCLUSION:We proposed here new criteria to select patients with adverse clinical outcomes after appendectomy among the patients with radiologically nonperforated appendicitis.Surgical appendectomy outcomes could be improved by determining the surgical priority according to our criteria.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2022R1F1A1068828).
文摘Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the same person within one image,but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same.When tracking the same object using two or more images,there must be a way to determine that objects existing in different images are the same object.Therefore,this paper attempts to determine the same object present in different images using color information among the unique information of the object.Thus,this study proposes a multiple-object-tracking method using histogram stamp extraction in closed-circuit television applications.The proposed method determines the presence or absence of a target object in an image by comparing the similarity between the image containing the target object and other images.To this end,a unique color value of the target object is extracted based on its color distribution in the image using three methods:mean,mode,and interquartile range.The Top-N accuracy method is used to analyze the accuracy of each method,and the results show that the mean method had an accuracy of 93.5%(Top-2).Furthermore,the positive prediction value experimental results show that the accuracy of the mean method was 65.7%.As a result of the analysis,it is possible to detect and track the same object present in different images using the unique color of the object.Through the results,it is possible to track the same object that can minimize manpower without using personal information when detecting objects in different images.In the last response speed experiment,it was shown that when the mean was used,the color extraction of the object was possible in real time with 0.016954 s.Through this,it is possible to detect and track the same object in real time when using the proposed method.
