Evaluation of a New Smartphone Powered Low-cost Pulse Oximeter Device.

Background: Measurement of blood oxygen saturation is a vital part of monitoring coronavirus 2019 (COVID-19) patients. Pulse oximetry is commonly used to measure blood oxygen saturation and pulse rate for appropriate clinical intervention. But the majority of direct-to-consumer grade pulse oximeters did not pass through in-vivo testing, which results in their accuracy being questionable.

Development of Low-Cost and Portable Pulse Oximeter Device with Improved Accuracy and Accessibility.

Purpose: In a clinical setting, blood oxygen saturation is one of the most important vital sign indicators. A pulse oximeter is a device that measures the blood oxygen saturation and pulse rate of patients with various disorders. However, due to ethical concerns, commercially available pulse oximeters are limited in terms of calibration on critically sick patients, resulting in a significant error rate for measurement in the critical oxygen saturation range.

De-Speckling Breast Cancer Ultrasound Images Using a Rotationally Invariant Block Matching Based Non-Local Means (RIBM-NLM) Method.

The ultrasonic technique is an indispensable imaging modality for diagnosis of breast cancer in young women due to its ability in efficiently capturing the tissue properties, and decreasing nega-tive recognition rate thereby avoiding non-essential biopsies. Despite the advantages, ultrasound images are affected by speckle noise, generating fine-false structures that decrease the contrast of the images and diminish the actual boundaries of tissues on ultrasound image. Moreover, speckle noise negatively impacts the subsequent stages in image processing pipeline, such as edge detec-tion, segmentation, feature extraction, and classification.

Accurate Machine-Learning-Based classification of Leukemia from Blood Smear Images.

Background: Conventional identification of blood disorders based on visual inspection of blood smears through microscope is time consuming, error-prone and is limited by hematologist's physical acuity. Therefore, an automated optical image processing system is required to support the clinical decision-making.

Materials And Methods: Blood smear slides (n = 250) were prepared from clinical samples, imaged and analyzed in Jimma Medical Center, Hematology department.