Obturator hernia is rare. It occurs when part of the pelvic contents protrude through the obturator foramen. It is a diagnostic challenge in the emergency department since the signs and symptoms are non-specific. It often occurs in elderly, emaciated and chronically ill women. The clinical picture include intestinal obstruction with abdominal pain, nausea and vomiting. The treatment is only surgical. Delayed diagnosis of this condition usually leads to a high mortality rate. We report the case of an 83-year-old woman with a strangulated obturator hernia. The hernia was discovered early by computed tomography and was treated by emergency laparotomy. We emphasize on the rule of CT scan to establishing a prompt preoperative diagnosis of an obturator hernia, appropriate planning of surgical intervention and thus optimizing the outcome.
The right ventricular assessment is crucial to heart disease diagnosis. Unfortunately, its segmentation is quite challenging due to its intricate shape, ill-defined thin edges, large variability among patients, and pathologies. Besides, it is a very laborious and time-consuming task to be done manually. Therefore, automated segmentation techniques are very suitable to reduce the strain on the expert. Here, it is attempted to review the taxonomy of the current RV segmentation approaches adopted to handle the afore-mentioned issues. Enhanced by our expert's interpretation, the results of over forty research papers were evaluated based on several metrics such as the dice metric and the Hausdorff distance. Synthetic tables and charts were also used to discuss the reviewed approaches. The following study shows that none of the existing methods has proved accurate enough to meet all the RV challenging issues. Many misestimated results were reported for several cases. Eventually, global guidance is outlined, which supports combining different methods to enhance the expected results during the MRI short-axis slice processing.
Magnetic Resonance Imaging (MRI) has emerged as the golden reference for cardiac examination. This modality allows the assessment of human cardiovascular morphology, functioning, and perfusion. Although a couple of challenging issues, such as the cardiac MR image's features and the large variability of images among several patients, still influences the cardiac cavities' segmentation and needs to be carried out. In this paper, we have profoundly reviewed and fully compared semi-automated segmentation methods performed on cardiac Cine-MR short-axis images for the evaluation of the left ventricular functions. However, the number of parameters handled by the synthesized works is limited if not null. For the sake of ensuring the highest coverage of the LV parameters computing, we have introduced a parallel watershedbased approach to segment the left ventricular allowing hence the computation of six parameters (End-Diastolic Volume, End-Systolic Volume, Ejection Fraction, Cardiac output, Stroke Volume and Left Ventricular Mass). An algorithm is associated with main considered measurements. The experimental results that were obtained through studying twenty patients' MRI data base, demonstrate the accuracy of our approach for estimating real values of the maximal set of parameters thanks to a faithful segmentation of the myocardium.
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