Tumors of Maxillary Salivary Glands

AIM OF THE STUDY: Salivary gland tumors constitute 3% of all head and neck malignancies. Tumors of minor salivary gland constitute 9-23%. Minor salivary glands are distributed throughout the oral cavity and also in paranasal sinuses. Tumors of maxillary salivary glands are heterogeneous in nature, the etiology of which remains unclear.The aim of this study is to evaluate the surgical,surgical and radiotherapeutic outcome, recurrence and prognosis in patients with maxillary salivary glands tumors. METHODOLOGY: This study is a prospective and retrospective study of tumors of maxillary salivary glands. The study spreads from 2008-2014. Fifteen patients were treated in our institution, eight patients were males and six patients were females. Adenoid cystic carcinoma represented 6 cases. Mucoepidermoid carcinoma represented 3 cases. Pleomorphic adenoma and inverted papilloma represented 2 cases each. Polymorphous low grade adenocarcinoma and carcinoma EX pleomorphic adenoma represented 1 case each. 11 cases underwent maxillectomy, 4 cases underwent wide local excision. The patients were followed up and details regarding surgical, surgical radiotherapeutic outcomes, recurrence and prognosis were evaluated. RESULTS: Palatal tumors are more aggressive. Adenoid cystic carcinoma is associated with distant metastasis and perineural invasion. Mucoepidermoid carcinoma is associated with recurrence. Clear 3-dimensional surgical margins results in good prognosis. T-stage does not influence the surgical outcome. The tumor involvement of nerve, bone, soft tissue and the grade of tumor influence the surgical outcome. CONCLUSION: Any palatal tumor must be considered as minor salivary gland tumor until proven otherwise. Earlier the treatment initiated better is the prognosis. Radiotherapy must be included in the treatment of minor salivary gland tumors, so as not to miss any therapeutic benefits, even though controversies exist

A Study on RGB Image Multi-Thresholding using Kapur/Tsallis Entropy and Moth-Flame Algorithm

In the literature, a considerable number of image processing and evaluation procedures are proposed and implemented in various domains due to their practical importance. Thresholding is one of the pre-processing techniques, widely implemented to enhance the information in a class of gray/RGB class pictures. The thresholding helps to enhance the image by grouping the similar pixels based on the chosen thresholds. In this research, an entropy assisted threshold is implemented for the benchmark RGB images. The aim of this work is to examine the thresholding performance of well-known entropy functions, such as Kapur’s and Tsallis for a chosen image threshold. This work employs a Moth-Flame-Optimization (MFO) algorithm to support the automatic identification of the finest threshold (Th) on the benchmark RGB image for a chosen threshold value (Th=2,3,4,5). After getting the threshold image, a comparison is performed against its original picture and the necessary Picture-Quality-Values (PQV) is computed to confirm the merit of the proposed work. The experimental investigation is demonstrated using benchmark images with various dimensions and the outcome of this study confirms that the MFO helps to get a satisfactory result compared to the other heuristic algorithms considered in this study

Partial Image Enhancement by Re-sampling of Pixels using Image Enhancement Techniques

With the advent of modern Technologies in the field of Photography, Photographs are playing an eminent role in our lives. But as the time rolls, Photographs gets antiquated and vile. So there is a need to enhance the Photographs such that they render the desired characteristics. Sometimes there may be a case where there is a need to render manipulations to a specific portion of the Image without disturbing the remaining part of the image. This paper operates on this issue and presents a reliable solution so that modifications are rendered to a specific part of an image. This paper focuses on choosing the portion of the image where the manipulations are to be furnished, applying the Image Enhancement Techniques to that portion of the image and Re-sampling the pixel values of the original image with the pixel values of that enhanced image at the exact coordinates where the portion of the image has been chosen. The resultant Image will be an image similar to the original image other than the modifications made to the specific part of the image. Rather than as a Digital Image Editor, this paper would be well exploited when you want to render modifications to the specific part of an image, while the remaining portion of the image is unaltere

Automatic detection of tuberculosis using VGG19 with seagull-algorithm.

Due to various reasons, the incidence rate of communicable diseases in humans is steadily rising, and timely detection and handling will reduce the disease distribution speed. Tuberculosis (TB) is a severe communicable illness caused by the bacterium Mycobacterium-Tuberculosis (M. tuberculosis), which predominantly affects the lungs and causes severe respiratory problems. Due to its significance, several clinical level detections of TB are suggested, including lung diagnosis with chest X-ray images. The proposed work aims to develop an automatic TB detection system to assist the pulmonologist in confirming the severity of the disease, decision-making, and treatment execution. The proposed system employs a pre-trained VGG19 with the following phases: (i) image pre-processing, (ii) mining of deep features, (iii) enhancing the X-ray images with chosen procedures and mining of the handcrafted features, (iv) feature optimization using Seagull-Algorithm and serial concatenation, and (v) binary classification and validation. The classification is executed with 10-fold cross-validation in this work, and the proposed work is investigated using MATLAB® software. The proposed research work was executed using the concatenated deep and handcrafted features, which provided a classification accuracy of 98.6190% with the SVM-Medium Gaussian (SVM-MG) classifier

Social group optimization–assisted Kapur's entropy and morphological segmentation for automated detection of COVID-19 infection from computed tomography images

The coronavirus disease (COVID-19) caused by a novel coronavirus, SARS-CoV-2, has been declared a global pandemic. Due to its infection rate and severity, it has emerged as one of the major global threats of the current generation. To support the current combat against the disease, this research aims to propose a machine learning–based pipeline to detect COVID-19 infection using lung computed tomography scan images (CTI). This implemented pipeline consists of a number of sub-procedures ranging from segmenting the COVID-19 infection to classifying the segmented regions. The initial part of the pipeline implements the segmentation of the COVID-19–affected CTI using social group optimization–based Kapur's entropy thresholding, followed by k-means clustering and morphology-based segmentation. The next part of the pipeline implements feature extraction, selection, and fusion to classify the infection. Principle component analysis–based serial fusion technique is used in fusing the features and the fused feature vector is then employed to train, test, and validate four different classifiers namely Random Forest, K-Nearest Neighbors (KNN), Support Vector Machine with Radial Basis Function, and Decision Tree. Experimental results using benchmark datasets show a high accuracy (> 91%) for the morphology-based segmentation task; for the classification task, the KNN offers the highest accuracy among the compared classifiers (> 87%). However, this should be noted that this method still awaits clinical validation, and therefore should not be used to clinically diagnose ongoing COVID-19 infection

Spray Drying as an Approach for Enhancement of Dissolution and Bioavailability of Raloxifene Hydrochloride.

The present study investigated the effect of spray drying raloxifene HCl (RHCL) with different classes of hydrophilic carriers (different grades of polyvinyl pyrrolidones) and cellulosic polymers) in order to determine the potential effect on dissolution rate and bioavailability of RHCL. Pre-formulation studies were conducted to select the appropriate carriers and drug:carrier ratio for preparing the spray dried compositions.The solid state interactions of the spray dried mixtures were evaluated by DSC & XRD. Preformulation studies revealed that amorphous compositions of RHCL could be obtained only with Plasdones (K12, K29/32 and S630). DSC studies showed that the crystalline nature of RHCL was significantly reduced on spray drying. Significant enhancement in dissolution rate was observed with the prepared spray dried compositions and out of the three grades of Plasdone, Plasdone K12 demonstrated the maximum enhancement in rate of release of RHCL. The pharmacokinetics of spray dried composition (1:1 RHCL: K12) and pure RHCL was evaluated following oral administration (25 mg/kg) in healthy female Sprague Dawley rats. The extent of the mean plasma exposures of RHCL was 7-fold higher in animals treated with spray dried mixture of RHCL, K12 (1:1) compared to animals treated with RHCL. Spray drying of RHCL with Plasdones, especially Plasdone K12, reduced drug crystallinity, increased the rate and extent of dissolution, and improved bioavailability

Sustainable Agro-Food Industrial Wastewater Treatment Using High Rate Anaerobic Process

This review article compiles the various advances made since 2008 in sustainable high-rate anaerobic technologies with emphasis on their performance enhancement when treating agro-food industrial wastewater. The review explores the generation and characteristics of different agro-food industrial wastewaters; the need for and the performance of high rate anaerobic reactors, such as an upflow anaerobic fixed bed reactor, an upflow anaerobic sludge blanket (UASB) reactor, hybrid systems etc.; operational challenges, mass transfer considerations, energy production estimation, toxicity, modeling, technology assessment and recommendations for successful operation

Sustainable Agro-Food Industrial Wastewater Treatment Using High Rate Anaerobic Process

This review article compiles the various advances made since 2008 in sustainable high-rate anaerobic technologies with emphasis on their performance enhancement when treating agro-food industrial wastewater. The review explores the generation and characteristics of different agro-food industrial wastewaters; the need for and the performance of high rate anaerobic reactors, such as an upflow anaerobic fixed bed reactor, an upflow anaerobic sludge blanket (UASB) reactor, hybrid systems etc.; operational challenges, mass transfer considerations, energy production estimation, toxicity, modeling, technology assessment and recommendations for successful operation

Sustainable Agro-Food Industrial Wastewater Treatment Using High Rate Anaerobic Process

This review article compiles the various advances made since 2008 in sustainable high-rate anaerobic technologies with emphasis on their performance enhancement when treating agro-food industrial wastewater. The review explores the generation and characteristics of different agro-food industrial wastewaters; the need for and the performance of high rate anaerobic reactors, such as an upflow anaerobic fixed bed reactor, an upflow anaerobic sludge blanket (UASB) reactor, hybrid systems etc.; operational challenges, mass transfer considerations, energy production estimation, toxicity, modeling, technology assessment and recommendations for successful operation