Automated Diagnosis and Assessment of Cardiac Structural Alteration in Hypertension Ultrasound Images.

Hypertension (HTN) is a major risk factor for cardiovascular diseases. At least 45% of deaths due to heart disease and 51% of deaths due to stroke are the result of hypertension. According to research on the prevalence and absolute burden of HTN in India, HTN positively correlated with age and was present in 20.

Novel Radiomics Features for Automated Detection of Cardiac Abnormality in Patients with Pacemaker.

Cardiac pacemakers are used in the treatment of patients with symptomatic bradycardia. The pacemaker paces the heart at the predetermined rate to maintain uninterrupted cardiac activity. Usually, pacemaker lead will be connected to the right atrium (RA) and right ventricle (RV) in dual-chamber pacemaker implantation and RV alone in single-chamber pacemaker implantation.

A practical artificial intelligence system to diagnose COVID-19 using computed tomography: A multinational external validation study.

Computed tomography has gained an important role in the early diagnosis of COVID-19 pneumonia. However, the ever-increasing number of patients has overwhelmed radiology departments and has caused a reduction in quality of services. Artificial intelligence (AI) systems are the remedy to the current situation.

Cortical Bone Mechanical Assessment via Free Water Relaxometry at 3 T.

Background: Investigation of cortical bone using magnetic resonance imaging is a developing field, which uses short/ultrashort echo time (TE) pulse sequences to quantify bone water content and to obtain indirect information about bone microstructure.

Purpose: To improve the accuracy of the previously proposed technique of free water T quantification and to seek the relationship between cortical bone free water T and its mechanical competence.

Study Type: Prospective.

Accurate automated diagnosis of carpal tunnel syndrome using radiomics features with ultrasound images: A comparison with radiologists' assessment.

Purpose: Ultrasonography is the most common imaging modality used to diagnose carpal tunnel syndrome (CTS). Recently artificial intelligence algorithms have been used to diagnose musculoskeletal diseases accurately without human errors using medical images. In this work, a computer-aided diagnosis (CAD) system is developed using radiomics features extracted from median nerves (MN) to diagnose CTS accurately.

Z-scan method to measure the nonlinear optical behavior of cells for evaluating the cytotoxic effects of chemotherapy and hyperthermia treatments.

The effects of new treatments must be investigated in vitro before using clinically or in vivo. The aim of this study was to introduce the Z-scan technique as a fast, accurate, inexpensive, and safe in vitro method to distinguish the cytotoxic effects of various treatments. C6 and OLN-93 cell lines were prepared and treated with Temozolomide (TMZ), radiofrequency hyperthermia (HT), and chemo-hyperthermia (HT+TMZ).

Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks.

Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in high workload conditions. Although a laboratory test is the current routine diagnostic tool, it is time-consuming, imposing a high cost and requiring a well-equipped laboratory for analysis. Computed tomography (CT) has thus far become a fast method to diagnose patients with COVID-19.

Magneto-plasmonic nanoparticle mediated thermo-radiotherapy significantly affects the nonlinear optical properties of treated cancer cells.

In order to determine the level of cell damage in cancerous cells, current cytogenetic tests have limitations such as time consumption and high cost. The aim of this study was to demonstrate the ability of nonlinear refractive (NLR) index as a predictor of breast cell damage caused by magneto-plasmonic nanoparticle based thermo-radiotherapy treatments. MCF-7 breast cancer cells were subjected individually to the treatment of radiation, radio-frequency (RF) hyperthermia, and radiation + RF hyperthermia.

The capability of nonlinear optical characteristics as a predictor for cellular uptake of nanoparticles and cell damage.

Current methods for determining the cellular effects of a treatment modality need expensive materials and much time to provide a researcher with results. The aim of this study was to evaluate the potential of nonlinear optical characteristics of cancer cells using Z-scan technique to monitor the level of cellular uptake and cell damage caused by a nanotechnology based treatment modality. Two nanocomplexes were synthesized and characterized.

Evaluation of nonlinear optical behavior of mouse colon cancer cell line CT26 in hyperthermia treatment.

Hyperthermia treatment can induce component changes on cell. This study explored the potential of Z-scan to improve accuracy in the identification of subtle differences in mouse colon cancer cell line CT26 during hyperthermia treatment. Twenty-one samples were subjected individually to treatment of hyperthermia at 41, 43, and 45 °C.

Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis.

Purpose: Papillary thyroid carcinoma (PTC) is the most common thyroid cancer, and cervical lymph nodes (LNs) are the most common extrathyroid metastatic involvement. Early detection and reliable diagnosis of LNs can lead to improved cure rates and management costs. This study explored the potential of texture analysis for texture-based classification of tumour-free and metastatic cervical LNs of PTC in ultrasound imaging.

Scintigraphic texture analysis for assessment of renal allograft function.

Purpose: Early detection and monitoring of kidney function during the post-transplantation period is one of the most important issues for improving the accuracy of an initial diagnosis. The aim of this study was to evaluate texture analysis (TA) in scintigraphic imaging to detect changes in kidney status after transplantation.

Material And Methods: Scintigraphic images were used for TA from a total of 94 kidney allografts (39 rejected and 55 non-rejected).

Evaluation of nonlinear optical differences between breast cancer cell lines SK-BR-3 and MCF-7; an in vitro study.

Background: This study aimed to explore the potential of the Z-scan technique to improve accuracy in identifying SK-BR-3 and MCF-7 breast cancer cell lines.

Methods: Three in vitro samples were prepared for each breast cancer cell line. A closed-aperture Z-scan technique was used to measure the sign and magnitude of the nonlinear refractive index of each sample.

Predictive quantitative sonographic features on classification of hot and cold thyroid nodules.

Purpose: This study investigated the potentiality of ultrasound imaging to classify hot and cold thyroid nodules on the basis of textural and morphological analysis.

Methods: In this research, 42 hypo (hot) and 42 hyper-function (cold) thyroid nodules were evaluated through the proposed method of computer aided diagnosis (CAD) system. To discover the difference between hot and cold nodules, 49 sonographic features (9 morphological, 40 textural) were extracted.

Classification of Benign and Malignant Thyroid Nodules Using Wavelet Texture Analysis of Sonograms.

Objectives: The purpose of this study was to evaluate a computer-aided diagnostic system using texture analysis to improve radiologic accuracy for identification of thyroid nodules as malignant or benign.

Methods: The database comprised 26 benign and 34 malignant thyroid nodules. Wavelet transform was applied to extract texture feature parameters as descriptors for each selected region of interest in 3 normalization schemes (default, μ ± 3σ, and 1%-9%).

Classification of breast tumors using sonographic texture analysis.

Objectives: The purpose of this study was to evaluate a computer-aided diagnostic system with texture analysis to improve radiologists' accuracy in identification of breast tumors as malignant or benign.

Methods: The database included 20 benign and 12 malignant tumors. We extracted 300 statistical texture features as descriptors for each selected region of interest in 3 normalization schemes (default, μ - 3σ, and μ + 3σ, where μ and σ were the mean value and standard deviation, respectively, of the gray-level intensity and 1%-99%).