Tuberculosis is a chronic granulomatous systemic infectious disease caused by Mycobacterium tuberculosis. The oral lesions found in tuberculosis are relatively rare and may present as ulcers, erythematous patches, indurated lesions, nodules or as bony jaw lesions. Oral tubercular lesions sometimes present a confusing clinical presentation and can be overlooked. Hence, we document a case of tuberculous osteomyelitis of the maxilla in a 19-year-old female patient, who was initially treated for multiple periodontal dental abscesses, which later proved to be tubercular osteomyelitis of the maxilla. Although it is a rare occurrence, the differential diagnosis of tuberculous osteomyelitis must always be considered when it fails to respond to routine therapy.
Granulicatella adiacens is a nutritionally variant streptococcus species. These bacteria are rarely isolated in the laboratory due to their fastidious growth requirements. These have been mostly reported from bloodstream infections, infective endocarditis, infections of orbit, nasolacrimal duct and breast implants. Here, we are reporting two cases of subcutaneous abscesses caused by G. adiacens. In first case, it was isolated from abscess around elbow joint and second case was a suprapatellar abscess. We have also reviewed the published data concerning diagnosis and antimicrobial susceptibility pattern of Granulicatella infections and included some Indian cases.
As multimedia technology is developing and growing these days, the use of an enormous number of images and its datasets is likewise expanding at a quick rate. Such datasets can be utilized for the purpose of image retrieval. This research focuses on extraction of similar images established on its different features for the image retrieval purpose from huge dataset of images. In this paper initially, the query image is searched within the available dataset and, then, the color difference histogram (CDH) descriptor is employed to retrieve the images from database. The basic characteristic of CDH is that it counts the color difference stuck among two distinct labels in the L ∗ a ∗ b ∗ color space. This method is experimented on random images used for various medical purposes. Various unlike features of an image are extracted via different distance methods. The precision rate, recall rate, and F-measure are all used to evaluate the system’s performance. Comparative analysis in terms of F-measure is also made to check for the best distance method used for retrieval of images.
Automated segmentation and delineation of morphological properties of retinal vascular network had now become the most important research area in the treatment of ophthalmologic disorders. With the advancement of computational efficiency, image processing methodologies are widely used in ophthalmology. This paper gives the review of various segmentation techniques implemented by various authors in conjunction with performance metrics like sensitivity, specificity, accuracy and area under the curve. Results of various algorithms has been compared and analyzed. For the extraction of retinal vasculature, 2D retinal image from various databases has been considered.
The routine dental practice involves various dental procedures which needs the application of local anesthetics. Generally, there are very few complications associated with these procedures. Complications such as tissue necrosis can occur following the rapid injection of local anesthetic solutions. Palate is a favorable site for soft tissue lesions, various factors such as direct effects of the drug, blanching of the tissues during injection, a relatively poor blood supply, and reactivation of the latent forms of herpes can all promote to tissue ischemia and a lesion in the palate.
This paper focuses on retrieving plant leaf images based on different features that can be useful in the plant industry. Various images and their features can be used to identify the type of leaf and its disease. For this purpose, a well-organized computer-assisted plant image retrieval approach is required that can use a hybrid combination of the color and shape attributes of leaf images for plant disease identification and botanical gardening in the agriculture sector. In this research work, an innovative framework is proposed for the retrieval of leaf images that uses a hybrid combination of color and shape features to improve retrieval accuracy. For the color features, the Color Difference Histograms (CDH) descriptor is used while shape features are determined using the Saliency Structure Histogram (SSH) descriptor. To extract the various properties of leaves, Hue and Saturation Value (HSV) color space features and First Order Statistical Features (FOSF) features are computed in CDH and SSH descriptors, respectively. After that, the HSV and FOSF features of leaf images are concatenated. The concatenated features of database images are compared with the query image in terms of the Euclidean distance and a threshold value of Euclidean distance is taken for retrieval of images. The best results are obtained at the threshold value of 80% of the maximum Euclidean distance. The system’s effectiveness is also evaluated with different performance metrics like precision, recall, and F-measure, and their values come out to be respectively 1.00, 0.96, and 0.97, which is better than individual feature descriptors.
A woman, aged 36, was admitted to hospital with major vaginal bleeding. She had cirrhosis caused by hepatitis C and had been previously treated with band ligation for recurrent bleeds from esophageal varices. She also had an episode of bleeding from varices in the small bowel that settled with conservative management including splanchnic vasoconstrictor therapy. Additional past history included a hysterectomy. The vaginal bleeding was controlled with vaginal packing, infusion of blood products and ligation of a bleeding lesion in the vaginal wall. However, episodes of vaginal bleeding continued over the subsequent 3 weeks. A contrast-enhanced computed tomography scan showed large pelvic varices and these were confirmed by the presence of prominent veins at vaginoscopy (Figure 1). Because of continued major bleeding, transjugular portal venography was performed. There was a portosystemic gradient of 11 mmHg with extensive pelvic varices associated with the inferior mesenteric vein (Figure 2 left).A 10 x 80 mm portosystemic shunt (TIPS) was then deployed that extended from the right portal vein through the right hepatic vein and into the inferior vena cava (Figure 2 right). This was followed by embolization of the pelvic varices with foamed fibrovein sclerosant. Since the procedure, the patient has remained well with no further bleeding from portal hypertension.The gastro-esophageal region is the most common area for portal hypertensive hemorrhage. Varices that occur outside of this area are often called "ectopic" varices, but these only account for a minority (5%) of all episodes of variceal bleeding. The more common sites for bleeding ectopic varices include gastrointestinal stomas (30%), duodenum (20%), jejunum and ileum (20%), colon and rectum (8%) and peritoneum (10%). Vaginal variceal bleeding appears to be rare as there are only 7 case reports in the medical literature. Most of these patients have had a hysterectomy, presumably with the development of post-surgical collaterals. The initial management of vaginal varices consists of resuscitation and local control with tamponade. This is the third patient in the medical literature who has been treated with TIPS but other options include balloon-occluded retrograde transvenous obliteration and liver transplantation. For patients with active bleeding who are not appropriate for TIPS, the transhepatic approach to the portal vein is usually preferred because of more rapid access into the mesenteric venous system.
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