CASE-CF: Context Aware Smart Epidemic Control Framework.

Novel Coronavirus (COVID-19) has become one of the deadliest pandemics that has affected almost all the nations in the world. Lockdown and systematic re-opening of shopping malls, offices, etc. is still one of the major weapons against this virus. However, the government and medical agencies take long time to reopen the places due to risks involved in this deadly virus. The delay to reopen places has resulted in sharp decline in the growth of economy. In this paper a current context aware framework is proposed which uses multiple inputs for a specific region to decide whether to open it or not. The proposed framework used series of deep neural network models to generate recommendations specific to a particular region. Most of the inputs are real-time and readily available with the government. The main aim is to develop framework which can be used in any kind of pandemic even in small region to easily contain it. However, it has been tested using opensource data available for COVID-19. Data was crawled from web for 22 districts of Haryana state of India. Experimental result proved the efficiency of proposed framework.

A method for probabilistic mapping between protein structure and function taxonomies through cross training.

BACKGROUND: Prediction of function of proteins on the basis of structure and vice versa is a partially solved problem, largely in the domain of biophysics and biochemistry. This underlies the need of computational and bioinformatics approach to solve the problem. Large and organized latent knowledge on protein classification exists in the form of independently created protein classification databases. By creating probabilistic maps between classes of structural classification databases (e.g. SCOP) and classes of functional classification databases (e.g. PROSITE), structure and function of proteins could be probabilistically related. RESULTS: We demonstrate that PROSITE and SCOP have significant semantic overlap, in spite of independent classification schemes. By training classifiers of SCOP using classes of PROSITE as attributes and vice versa, accuracy of Support Vector Machine classifiers for both SCOP and PROSITE was improved. Novel attributes, 2-D elastic profiles and Blocks were used to improve time complexity and accuracy. Many relationships were extracted between classes of SCOP and PROSITE using decision trees. CONCLUSION: We demonstrate that presented approach can discover new probabilistic relationships between classes of different taxonomies and render a more accurate classification. Extensive mappings between existing protein classification databases can be created to link the large amount of organized data. Probabilistic maps were created between classes of SCOP and PROSITE allowing predictions of structure using function, and vice versa. In our experiments, we also found that functions are indeed more strongly related to structure than are structure to functions.

A high spatial resolution 1H magnetic resonance spectroscopic imaging technique for breast cancer with a short echo time.

The high sensitivity but low specificity of breast MRI has prompted exploration of breast (1)H MRS for breast cancer detection. However, several obstacles still prevent the routine application of in vivo breast (1)H MRS, including poor spatial resolution, long acquisition time associated with conventional multi-voxel MRS imaging (MRSI) techniques, and the difficulty of "extra" lipid suppression in a magnetic field with relatively poor achievable homogeneity compared to the brain. Using a combination of a recently developed echo-filter (EF) suppression technique and an elliptical sampling scheme, we demonstrate the feasibility of overcoming these difficulties. It is robust (the suppression technique is insensitive to magnetic field inhomogeneity), fast (acquisition time of about 12 min) and offers high spatial resolution (up to 0.6 cm(3) per voxel at 1.5 T with a TE of only 60 ms). This approach should be even better at 3 T with higher resolution and/or shorter TE.

New techniques in cerebral imaging.

This article presents a review of the current techniques in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) that enhance the usefulness of these tests for the diagnosis of cerebral disease. We were able to analyze concepts and definitions and give a comparative description for each test studied including Multidetector/Perfusion CT, Xenon CT, CT-Angiogram, MRI-Perfusion, MRI-Diffusion, MRI-Spectroscopy, MRI CSF Flow, Functional MRI studies and Cerebral Angiography.

Spectral pattern of total creatine and trimethyl ammonium in multiple sclerosis.

Fatigue and impairment mobility are frequent problems in multiple sclerosis (MS). Despite its enormous potential, in vivo (1)H MRS of skeletal muscles for MS patients is a largely unexplored field. One fundamental question remains unanswered: whether MS can cause observable proton metabolite changes. High quality two-dimensional in vivo (1)H MRS reveals that the spectral pattern of total creatine (tCr) and trimethyl ammonium (TMA) of soleus muscles of MS patients can be distinctively different from that of healthy volunteers, and in vivo (1)H MRS of skeletal muscles has a potential to become a useful tool in MS study.

Characterizing iron deposition in multiple sclerosis lesions using susceptibility weighted imaging.

PURPOSE: To investigate whether the variable forms of putative iron deposition seen with susceptibility weighted imaging (SWI) will lead to a set of multiple sclerosis (MS) lesion characteristics different than that seen in conventional MR imaging. MATERIALS AND METHODS: Twenty-seven clinically definite MS patients underwent brain scans using magnetic resonance imaging including: pre- and postcontrast T1-weighted imaging, T2-weighted imaging, FLAIR, and SWI at 1.5 T, 3 T, and 4 T. MS lesions were identified separately in each imaging sequence. Lesions identified in SWI were reevaluated for their iron content using the SWI filtered phase images. RESULTS: There were a variety of new lesion characteristics identified by SWI, and these were classified into six types. A total of 75 lesions were seen only with conventional imaging, 143 only with SWI, and 204 by both. From the iron quantification measurements, a moderate linear correlation between signal intensity and iron content (phase) was established. CONCLUSION: The amount of iron deposition in the brain may serve as a surrogate biomarker for different MS lesion characteristics. SWI showed many lesions missed by conventional methods and six different lesion characteristics. SWI was particularly effective at recognizing the presence of iron in MS lesions and in the basal ganglia and pulvinar thalamus.

New algorithm for quantifying vascular changes in dynamic contrast-enhanced MRI independent of absolute T1 values.

In this work, we present a new method for predicting changes in tumor vascularity using only one flip angle in dynamic contrast-enhanced (DCE) imaging. The usual DCE approach finds the tissue initial T1 value T1(0) prior to injection of a contrast agent. We propose finding changes in the tissue contrast agent uptake characteristics pre- and postdrug treatment by fixing T1(0). Using both simulations and imaging pre- and postadministration of caffeine, we find that the relative change (NR50) in the median of the cumulative distribution (R50) is almost independent of T1(0). Fixing T1(0) leads to a concentration curve c(t) more robust to the presence of noise than calculating T1(0). Consequently, the NR50 for the tumor remains roughly the same as the ideal NR50 when T1(0) is exactly known. Further, variations in eating habits are shown to create significant changes in the R50 response for both liver and muscle. In conclusion, analyzing data with fixed T1(0) leads to a more stable measure of changes in NR50 and does not require knowledge of T1(0). Both caffeine and eating introduce major changes in blood flow that can significantly modify the NR50 and lead to incorrect conclusions regarding drug treatment.

Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses.

PURPOSE: To evaluate the diagnostic value of susceptibility-weighted imaging (SWI) for studying brain masses. MATERIALS AND METHODS: SWI is a high-resolution, three-dimensional, fully velocity-compensated gradient-echo sequence that uses both magnitude and phase data. Custom postprocessing is applied to enhance the contrast in the magnitude images between tissues with different susceptibilities. This sequence was applied to 44 patients (24 males and 20 females, 15-89 years old, mean age = 50.3 years) with brain masses, pre- and/or postcontrast, and compared with conventional sequences (T1, T1 postcontrast, T2, proton density (PD), fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) at 1.5T). Correlation with pathology was obtained in 12 cases. All images were reviewed independently by three radiologists. RESULTS: In the evaluation of tumor visibility, boundary definition, blood products, venous vasculature, architecture, and edema, SWI gave better information than the standard T1-weighted postcontrast images in 11%, 14%, 71%, 73%, 63%, and 75% of the data, respectively, in a subgroup of 38 patients. This demonstrates that the information presented by SWI is complementary in nature to that available from conventional methods. On the whole, SWI was much more sensitive for showing blood products and venous vasculature. SWI showed a useful FLAIR-like contrast and complemented the information obtained by conventional T1 postcontrast sequences regarding the internal architecture of the lesions. Good pathologic correlations were found for blood products as predicted by SWI. CONCLUSION: SWI should prove useful for tumor characterization because of its ability to better highlight blood products and venous vasculature and reveal new internal architecture.

Clinical applications of neuroimaging with susceptibility-weighted imaging.

Susceptibility-weighted imaging (SWI) consists of using both magnitude and phase images from a high-resolution, three-dimensional, fully velocity compensated gradient-echo sequence. Postprocessing is applied to the magnitude image by means of a phase mask to increase the conspicuity of the veins and other sources of susceptibility effects. This article gives a background of the SWI technique and describes its role in clinical neuroimaging. SWI is currently being tested in a number of centers worldwide as an emerging technique to improve the diagnosis of neurological trauma, brain neoplasms, and neurovascular diseases because of its ability to reveal vascular abnormalities and microbleeds.