Feature-Based Classification of Mild Cognitive Impairment and Alzheimer's Disease Based on Optical Coherence Tomographic Angiographic Image.

Alzheimer's disease is a type of neurodegenerative disorder that is characterized by the progressive degeneration of brain cells, leading to cognitive decline and memory loss. It is the most common cause of dementia and affects millions of people worldwide. While there is currently no cure for Alzheimer's disease, early detection and treatment can help to slow the progression of symptoms and improve quality of life.

Biosensors for with Molecularly Imprinted Polymer (MIP) Technique.

Nosocomial infection is one of the most important problems that occurs in hospitals, as it directly affects susceptible patients or patients with immune deficiency. ( is the most common cause of nosocomial infections in hospitals. can cause various diseases such as pneumonia, urinary tract infections, septicemias, and soft tissue infections, and it has also become highly resistant to antibiotics.

Instance Segmentation of Multiple Myeloma Cells Using Deep-Wise Data Augmentation and Mask R-CNN.

Multiple myeloma is a condition of cancer in the bone marrow that can lead to dysfunction of the body and fatal expression in the patient. Manual microscopic analysis of abnormal plasma cells, also known as multiple myeloma cells, is one of the most commonly used diagnostic methods for multiple myeloma. However, as it is a manual process, it consumes too much effort and time.

Bone Mineral Density Screening System Using CMOS-Sensor X-ray Detector.

This research concerns a design and construction of a bone mineral density (BMD) and bone mineral content (BMC) measurement system based on dual energy X-ray absorptiometry (DEXA). An indirect X-ray detector is designed by optical coupling CMOS sensor with image on the intensifying screen. A dedicated microcontroller X-ray apparatus is used as an X-ray source to capture two energy level X-ray of middle phalanges bone of middle finger.

Optical-Based Foot Plantar Pressure Measurement System for Potential Application in Human Postural Control Measurement and Person Identification.

Plantar pressure, the pressure exerted between the sole and the supporting surface, has great potentialities in various research fields, including footwear design, biometrics, gait analysis and the assessment of patients with diabetes. This research designs an optical-based foot plantar pressure measurement system aimed for human postural control and person identification. The proposed system consists of digital cameras installed underneath an acrylic plate covered by glossy white paper and mounted with LED strips along the side of the plate.

Noninvasive Portable Hemoglobin Concentration Monitoring System Using Optical Sensor for Anemia Disease.

Anemia is a condition in which red blood cells are not able to carry adequate oxygen to the body's tissues, and is widely found in nearly a quarter of the world population. The typical method to screen for the iron-deficiency anemia, which is the major anemia found in the world, is to implement a blood test called a complete blood count (CBC). However, even though this test gives a highly accurate result, it requires an invasive blood drawing and lab analyzing which could potentially cause physical pain, high risk of infection and take a long time to analyze.

Multi-Parameter Vital Sign Telemedicine System Using Web Socket for COVID-19 Pandemics.

Telemedicine has become an increasingly important part of the modern healthcare infrastructure, especially in the present situation with the COVID-19 pandemics. Many cloud platforms have been used intensively for Telemedicine. The most popular ones include PubNub, Amazon Web Service, Google Cloud Platform and Microsoft Azure.

Automated Segmentation of Infarct Lesions in T1-Weighted MRI Scans Using Variational Mode Decomposition and Deep Learning.

Automated segmentation methods are critical for early detection, prompt actions, and immediate treatments in reducing disability and death risks of brain infarction. This paper aims to develop a fully automated method to segment the infarct lesions from T1-weighted brain scans. As a key novelty, the proposed method combines variational mode decomposition and deep learning-based segmentation to take advantages of both methods and provide better results.

Real-time multianalyte biosensors based on interference-free multichannel monolithic quartz crystal microbalance.

In this work, we design, fabricate and characterize a new interference-free multichannel monolithic quartz crystal microbalance (MQCM) platform for bio-sensing applications. Firstly, interference due to thickness-shear vibration mode coupling between channels in MQCM array is effectively suppressed by interposing a polydimethylsiloxane wall between adjacent QCM electrodes on a quartz substrate to form inverted-mesa-like structure. In addition, the electrical coupling due to the electrical impedance of solution is diminished by extending the flow path between them with an extended-design flow channel.

Use of computational fluid dynamics nasal airflow measurement to design septoplasty: a pilot study.

Deviation in the nasal septum that obstructs airflow is a source of discomfort to patients. Areas of nasal malformation then, need to be identified before performing surgery. In the present study, the authors introduce the computational fluid dynamic (CFD) technique to predict regions of limited airflow based on CT scan reconstruction of the nasal cavity.

Penalized-likelihood reconstruction for metal artifact reduction in cone-beam CT.

CT reconstruction from metal-embedded data usually produces streak artifacts that reduce the quality of the reconstructed images. In this paper, we propose a new technique for metal artifact reduction in cone-beam CT based on statistical reconstruction. First, the metal objects are segmented in the reconstructed images and then reprojected to obtain the measurement data of the metal objects using cone-beam reconstruction.

Invariant surface alignment in the presence of affine and some nonlinear transformations.

In this paper, we introduce a non-iterative geometric-based method to align 3D brain surfaces into standard coordinate system, which is based on a novel set of surface landmarks (e.g., inflection and/or zero torsion points residing on parabolic contours), which are intrinsic and are computed from the differential geometry of the surface.