Glaucoma is a major global cause of blindness. As the symptoms glaucoma appear, when disease reaches an advanced stage, proper screening in early stages challenging. Therefore, regular essential and recommended. However, eye currently subjective, time-consuming labor-intensive there are insufficient specialists available. We present automatic two-stage system to reduce workload ophthalmologists. The first segmented optic disc region using DeepLabv3+ architecture but substituted encoder...

Cervical cancer can be prevented by having regular screenings to find any precancers and treat them. The Pap test looks for abnormal or precancerous changes in the cells on cervix. However, manual screening of smear microscope is subjective with poorly reproducible criteria. Therefore, aim this study was develop a computer-assisted system cervical using digital image processing images. analysis important system. There were four basic steps our In cell segmentation, nuclei detected...

This paper proposes a novel algorithm to estimate log-compressed K distribution parameter and presents an discriminate breast tumors in ultrasonic images. We computed total of 208 features for discrimination, including those based on K-distribution, which quantifies the homogeneity echo pattern tumor, but is influenced by compression parameters device. The proposed estimates K-distribution manner free from this influence. To quantify irregularities tumor shape, pattern-spectrum-based were...

Cytological screening plays a vital role in the diagnosis of cancer from microscope slides pleural effusion specimens. However, this manual method is subjective and time-intensive it suffers inter- intra-observer variations. In study, we propose novel Computer Aided Diagnosis (CAD) system for detection cells cytological (CPE) images. Firstly, intensity adjustment median filtering methods were applied to improve image quality. Cell nuclei extracted through hybrid segmentation based on fusion...

In 3D medical imaging, anatomical and other structures such as kidney stones are often identified extracted with the aid of diagnosis assessment disease. Automatic stone segmentation from abdominal CT images is challenging on aspects accuracy due to its variety size, shape location. The performance organ algorithm also degraded by image complexity containing multiple organs because their huge size. current need a preprocessing assist process. objective present study was develop reader...

Caries prevention is essential for oral hygiene. A fully automated procedure that reduces human labor and error needed. This paper presents a method segments tooth regions of interest from panoramic radiograph to diagnose caries. patient's radiograph, which can be taken at any dental facility, first segmented into several individual teeth. Then, informative features are extracted the teeth using pre-trained deep learning network such as VGG, Resnet, or Xception. Each feature learned by...

This paper introduces the design and characterization of a double-stage energy harvesting floor tile that uses piezoelectric cantilever to generate electricity from human footsteps. A frequency up-conversion principle, in form an overshooting cantilever, plucked with proof mass is utilized increase conversion efficiency. The overshoot implemented by mechanical impact between moving cover plate stopper prevent damage element. In experiment, prototype was excited pneumatic actuator simulated...

Lung cancer is a life-threatening disease with the highest morbidity and mortality rates of any worldwide. Clinical staging lung can significantly reduce rate, because effective treatment options strongly depend on specific stage cancer. Unfortunately, manual remains challenge due to intensive effort required. This paper presents computer-aided diagnosis (CAD) method for detecting from computed tomography (CT) images. CAD works in three fundamental phases: segmentation, detection, staging....

Caries is the most well-known disease and relates to oral health of billions people around world. Despite importance necessity a well-designed detection method, studies in caries are still limited show restriction performance. In this paper, we proposed computer-aided diagnosis (CAD) method detect among normal patients using dental radiographs. The mainly consists two processes: feature extraction classification. phase, chosen 2D tooth image was employed extract deep activated features...

Electrocardiogram (ECG) has been actively proposed as an aliveness biometric for years. In realistic application, this type of biometrics still needs to be verified in some conditions related the practical use. Therefore, we propose paper study two themes that concern its application. First, single beat electrocardiogram (SB-ECG) is used ECG feature, which aims decrease time acquire from individual. Second, robustness features heart rate variability (HRV), investigate relation between...

Visually induced motion sickness (VIMS) is an important safety issue in stereoscopic 3D technology. Accompanying subjective judgment of VIMS with objective measurement useful to identify not only biomedical effects dynamic contents, but also provoking scenes that induce VIMS, duration and user behavior during VIMS. Heart rate variability depth gaze are appropriate physiological indicators for such observation. However, there no information about relationship between heart variability,...

Tuberculosis (TB) is a leading infectious killer, especially for people with Human Immunodeficiency Virus (HIV) and Acquired Syndrome (AIDS). Early diagnosis of TB crucial disease treatment control. Radiology fundamental diagnostic tool used to screen or triage TB. Automated chest x-rays analysis can facilitate expedite screening fast accurate reports radiological findings rapidly large populations alleviate shortage skilled experts in remote areas. We describe hybrid feature-learning...

The ongoing COVID-19 pandemic has caused devastating effects on humanity worldwide. With practical advantages and wide accessibility, chest X-rays (CXRs) play vital roles in the diagnosis of evaluation extent lung damages incurred by virus. This study aimed to leverage deep-learning-based methods toward automated classification from normal viral pneumonia CXRs, identification indicative regions biomarkers. Initially, we preprocessed segmented usingDeepLabV3+ method, subsequently cropped...

Biometric recognition is a critical task in security control systems. Although the face has long been widely accepted as practical biometric for human recognition, it can be easily stolen and imitated. Moreover, video surveillance, challenge to obtain reliable facial information from an image taken at distance with low-resolution camera. Gait, on other hand, recently used because gait not easy replicate, obtained camera distance. However, alone still constraints due its intrinsic factors. In...

Diabetic Retinopathy (DR) is the leading cause of blindness in working-age adults globally. Primary screening DR essential, and it recommended that diabetes patients undergo this procedure at least once per year to prevent vision loss. However, addition insufficient number ophthalmologists available, eye examination itself labor-intensive time-consuming. Thus, an automated method using retinal images proposed paper reduce workload primary process so may make effective treatment plans...

Automated cell nuclei segmentation is the most crucial step toward implementation of a computer-aided diagnosis system for cancer cells. Studies on automated analysis cytology pleural effusion images are few because lack reliable methods. Therefore, this paper presents comparative study twelve methods images. Each method involves three main steps: preprocessing, segmentation, and postprocessing. The preprocessing stages help enhancing image quality extracting regions from rest image,...

Motorbike detection is not a novel problem. However, as it common vehicle in most countries the world, there barely enough research on vision-based methods for motorbike detection, even more so dense clusters. In this work, we proposed method that able to overcome fair occlusions traffic images. The centered around robust model: convolutional neural network (CNN) with multiple layers. CNN model has been proven achieve state-of-the-art results vision tasks. Although having straightforward...

In this paper, we propose a framework for detection and classification of cervical cancer from pap smear images. Early accurate diagnosis can reduce the death rate patients. Pap or test is most popular technique early cancer. However, manual analysis labor intensive time consuming process which relies on expert cytologist. Hence, it needed to develop computer aided system make more reliable. The objective paper present an innovative idea applying random forest algorithm (RF) as feature...

Due to the close resemblance between overlapping and cancerous nuclei, misinterpretation of nuclei can affect final decision cancer cell detection. Thus, it is essential detect distinguish them from single ones for subsequent quantitative analyses. This paper presents a method automated detection classification appearing in cytology pleural effusion (CPE) images. The proposed system comprised three steps: candidate extraction, dominant feature nuclei. A maximum entropy thresholding...

The effective manual detection ECG arrhythmia is very important, but it tedious and time consume. Due to the signal, monitoring may have be carried out over several hours because volume of data enormous. This difficulty turns a high possibility analyst missing (or misreading) vital information. Therefore, computer-based analysis diseases can helpful in cardiologist's diagnoses. paper proposes an algorithm detect classify arrhythmia, which combined novel beat length selection, Discrete Cosine...

The detection of pulmonary nodules on computed tomography scans provides a clue for the early diagnosis lung cancer. Manual mandates heavy radiological workload as it identifies slice-by-slice. This paper presents fully automated nodule with three significant contributions. First, an seeded region growing is designed to segment regions from scans. Second, three-dimensional chain code algorithm implemented refine border segmented lungs. Lastly, inside lungs are detected using optimized random...