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COVID-19 is the world's most serious threat, affecting billions of people worldwide. Medical imaging, such as CT, has a lot of potential as an alternative to RT-PCR approach for significant judgement and disease control. As a result, automatic image segmentation is in high demand as a therapeutic decision aid. According to studies, medical images may be very useful for early screening since certain aspects of the image imply the existence of virus of COVID-19 and hence may be used as an efficient scanning tool. The proposed work presents a hybrid approach for efficient screening of COVID-19 using chest CT images implementing Hybrid Particle Swarm Optimised-Fuzzy C Means Clustering. The proposed method is tested on 15 chest CT images of COVID-19-infected patients and the results have been validated quantitatively by metrices such as entropy, contrast and standard deviation, which clearly outperforms the conventional Fuzzy C Means Clustering. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is the fourth leading cause of cancer-related death worldwide. Pancreatic tumours are characterised by a peculiar cell progression in intestinal enzymes and hormone-producing cells. Patients with pancreatic tumours have a shorter survival period depending on the type of tumour they have. Enhancing patient survival, diagnosing patients with malignant pancreatic tumours as soon as possible is the need of hour. The commonly used approach for diagnosis and clinical disease staging of pancreatic cancer is Computed Tomography (CT). However, because most abdominal CT images contain noise in addition to visceral fat in the vicinity of the pancreas, prompt detection is difficult, which requires an algorithm that distinguishes the anatomical structure clearly. This paper proposes, Particle Swarm Optimisation incorporating Split and Merge Segmentation to obtain enhanced CT images of pancreatic tumour. The image undergoes image processing procedures such as segmentation using PSO and fetch an enhanced output image with the help of gaussian filter. The algorithm outperforms Conventional PSO in terms of Entropy and Contrast, according to experimental results. The improved CT scans aid in the early detection and diagnosis of pancreatic cancer. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Pancreatic cancer is highly lethal as it grows, spreads rapidly and difficult to diagnose at its early stages. It can be identified through scan images. The tumorous images obtained from imaging techniques suffer from the drawback of cryptic data due to presence of unwanted noise and poor contrast. OBJECTIVE: To reduce the risk of pancreatic cancer, its detection and diagnosis at an early stage becomes crucial. METHODS: The proposed work encompasses the processing of CT scans of pancreatic tumor using classical and artificial intelligence based optimized edge detection techniques for optimization and detection of tumor. RESULTS: The simulation results are highly encouraging as evident from the far improved visibility of resultant images with Particle Swarm Optimization. CONCLUSION: The output image with PSO shows the quality enhanced CT images which helps in accurate detection and diagnosis of the pancreatic tumor at an early stage providing an aid in medical imaging. [ABSTRACT FROM AUTHOR]

Byline: Ajay. Sharma, Smita. Makrandi, Megha. Modi, Archana. Sharma, Yogesh. Marfatia Background: Immune reconstitution inflammatory syndrome (IRIS) is a paradoxical deterioration in clinical status in a patient on antiretroviral treatment [...]

Byline: Ajay. Sharma, Roshni. Vora, Megha. Modi, Archana. Sharma, Yogesh. Marfatia Background: The introduction of highly active antiretroviral therapy (HAART) has led to significant reduction in acquired immune deficiency syndrome [...]

Purpose of the study: Medical field has highly evolved with advancements in the technologies which prove to be beneficial for radiologists and patients for better diagnosis. The era of medical science provides best healthcare solutions with the help of medical images. Till now, 2D MRIs played a prominent role in early detection of disease but with latest technologies taking over the charge, 3D MRIs are highly effective and great in demand nowadays. With the aid of advanced techniques such as edge detection, segmentation and texture analysis on these images, the disease detection may become much easier. Materials and Methods: Texture of any image is recognized by distribution of gray levels in the neighborhood. The Texture Analysis plays an important role in study of medical images. It identifies the prominent features of an image and highlights the same using different feature extraction technique. In this paper, 3D MRI of human brain is considered and texture analysis based on Haralick's and GLCM texture features is performed. Haralick's feature explains the image intensities of each pixel and their relationship with neighborhood pixels. The entire data set consists of 40 brain tumor patients, out of which a sample has been depicted. Results: The analysis of different features such as Contrast, Correlation, Energy, Homogeneity and Entropy is carried out. Conclusion: Further, the study highlights about the highly useful features for early detection of brain tumor disease. [ABSTRACT FROM AUTHOR]

Stavudine (d4T) and zidovudine (AZT) belong to nucleoside reverse transcriptase inhibitor (NRTI) group of drugs and they are the core drugs with lamivudine (3TC) as the first-line therapy. d4T is reported to cause a number of long-term metabolic and morphologic adverse drug reactions (ADR). In this study, the incidence and pattern of ADR due to d4T and AZT were compared. Ninety cases on antiretroviral treatment (ART) were studied prospectively over a period of 2 years. Forty-two cases were on AZT-based regimen, and 48 cases were on d4T-based regimen. In all cases, baseline investigations, serum lipid profile and lactate levels (if required) were carried out. Cases were evaluated monthly, and investigations were repeated quarterly for any ADR. Out of the 42 cases on AZT-based regimen, 21 had ADR; while 23 out of the 48 cases on d4T had ADR. Anemia (42.8%) and nail hyperpigmentation (30.9%) were the commonest ADR due to AZT. Peripheral neuropathy (PN) (39.6%) was the commonest ADR with d4T, followed by lipodystrophy (LD) (22.9%). Change of therapy was required in 1 case on AZT with severe anemia and in 5 cases on d4T with LD, PN or lactic acidemia. The severe ADR with d4T needed a change of regimen to AZT in 5 cases. Moreover, d4T requires monitoring for long-term metabolic changes, which may lead to morphologic disfigurement which are particularly distressing to females. As the cost of both the regimens is now almost equal, preference should be given to AZT-based regimen. [ABSTRACT FROM AUTHOR]

Cutaneous manifestations of human immunodefi ciency virus (HIV) infection or acquired Immunodefi ciency syndrome (AIDS) can occur throughout all stages of infection. The dermatological complications of HIV and AIDS may be distressing to the patient and difficult for the dermatologist to diagnose and manage. The aim of this study was to examine the pattern of noninfectious cutaneous manifestations and their relationship with stage of HIV infection. Two hundred HIV-positive/AIDS cases attending Skin-STD clinic, Govt. Medical College, Vadodara, were thoroughly examined to find cutaneous manifestations. Skin, scalp and nails were thoroughly examined. One hundred twenty out of 200 cases had noninfectious cutaneous manifestations like pruritic papular eruption in 43 cases (35.8%), pigmentary changes in 10 cases (8.3%), seborrheic dermatitis in 5 cases (4.2%) and psoriasis in 4 cases (3.3%). Such presentations were more frequently observed in symptomatic/AIDS cases. Adverse drug reactions (ADRs) were observed in 15 cases. These include 6 out of 30 cases on antiretroviral therapy (ART) and 9 cases on other medications. Pemphigus vulgaris and acanthosis nigricans (AN) were seen as co-presentation, each in 1 case of AIDS. HIV-related cutaneous manifestations are very common and, if studied properly, can serve as diagnostic and prognostic markers. They may reflect involvement of internal organs. Many of the infectious and noninfectious manifestations respond well to antiretroviral therapy, which may not be feasible in resource-restricted setup. [ABSTRACT FROM AUTHOR]

The aim was to study the cutaneous adverse effects of nevirapine (NVP). One hundred ten patients on NVP based regimen were enrolled in the study and monitored for adverse reactions (ADR). A detailed history of every patient was taken including past history of antiretroviral treatment. All patients were clinically evaluated and treated for opportunistic infections. Three drug regimen (Zidovudine/ Stavudine + Lamivudine + NVP) was prescribed to all cases having CD4 count < 200 cells/mm3 or clinically symptomatic cases. NVP was given in a lead in dose (200 mg once daily) for initial 15 days. If no hypersensitivity was seen then dose was increased to 200 mg twice daily. NVP induced rash was observed in 13 cases (11.8%). Rash was the commonest ADR of NVP and was graded according to standard guidelines. Stevens Johnson syndrome (grade IV rash) was observed in 3 cases. In 7 cases NVP was substituted by Efavirenz (EFV) while 2 cases continued with 2 drugs due to lack of resources. Two cases stopped treatment. Clinicians should always start the NVP in lead-in dose and closely monitor patients on NVP based regimen especially during the first two months of therapy. [ABSTRACT FROM AUTHOR]