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Training of laparoscopic surgery in Virtual Reality (VR) environment has been proved as an effective step before clinical practice. Tracking the position of instruments in realtime is an essential part of developing a VR trainer. In this study, we used Microsoft Kinect and color markers instead of using similar traditional means such as mechanical sensors. The orientation and position of instruments...
The heart rate (HR) is one of the important indicators for observing the patient condition. Therefore, many estimation techniques for acquiring heart rate have been developed. The photoplethysmography (PPG) and electrocardiography (ECG) are the common measurement techniques for estimating the heart rate. However, they should contact on the human skin in order to estimate the accurate heart rate. In...
In this work, we propose a method that detects and tracks the tip of tools used in microsurgical training. This method can be used to provide valuable metrics regarding the surgeon's hand movement. It can benefit the training of surgeons, given the steep learning curve in microsurgery. Unlike past research, our tool tracking algorithm does not rely on color based measurements. Thus, it can be used...
An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm...
Asymmetry is one of key characteristics for early diagnosis of melanoma according to medical algorithms such as (ABCD, CASH etc.). Besides shape information, cues such as irregular distribution of colors and structures within the lesion area are assessed by dermatologists to determine lesion asymmetry. Motivated by the clinical practices, we have used Kullback-Leibler divergence of color histogram...
This paper deals with the segmentation of angiodysplasias in wireless capsule endoscopy images. These lesions are the cause of almost 10% of all gastrointestinal bleeding episodes, and its detection using the available software presents low sensitivity. This work proposes an automatic selection of a ROI using an image segmentation module based on the MAP approach where an accelerated version of the...
Retinal prosthetic devices can significantly and positively impact the ability of visually challenged individuals to live a more independent life. We describe a visual processing system which leverages image analysis techniques to produce visual patterns and allows the user to more effectively perceive their environment. These patterns are used to stimulate a retinal prosthesis to allow self guidance...
Surgery using a robotic system has proven to have significant potential but is still a highly challenging task for the surgeon. An eye surgery assistant has been developed to eliminate the problem of tremor caused by human motions endangering the outcome of ophthalmic surgery. In order to exploit the full potential of the robot and improve the workflow of the surgeon, providing the ability to change...
We presented a systematic study of how subject head motion affects pulse rate estimation using photoplethysmography from the subject's face. We evaluated the performance at various steps in the process, including object tracking, skin blob detection, pulse signal extraction and pulse rate estimation. We demonstrated that the signal-to-noise ratio of the power spectrum is a good indicator of signal...
Automated classification of retinal vessels in fundus images is the first step towards measurement of retinal characteristics that can be used to screen and diagnose vessel abnormalities for cardiovascular and retinal disorders. This paper presents a novel approach to vessel classification to compute the artery/vein ratio (AVR) for all blood vessel segments in the fundus image. The features extracted...
In this paper, we introduce a new tool, CEREBRA, to visualize the 3D network of human brain, extracted from the fMRI data. The tool aims to analyze the brain connectivity by representing the selected voxels as the nodes of the network. The edge weights among the voxels are estimated by considering the relationships among the voxel time series. The tool enables the researchers to observe the active...
Breast cancer is the most common malignant tumor in women worldwide. In recent years, there has been an increasing use of immunohistochemistry (the process of detecting the expression of certain proteins in cytological images) to obtain useful information for diagnosis. This paper presents an efficient algorithm that automatically detects breast cancer cell nuclei and divides them into two groups:...
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques...
Chronic skin diseases like eczema may lead to severe health and financial consequences for patients if not detected and controlled early. Early measurement of disease severity, combined with a recommendation for skin protection and use of appropriate medication can prevent the disease from worsening. Current diagnosis can be costly and time-consuming. In this paper, an automatic eczema detection and...
Wireless capsule endoscopy is a new technology in the realm of telemedicine that has many advantages over the traditional endoscopy systems. Transmitted images should help diagnosis of diseases of the gastrointestinal tract. Two important technical challenges for the manufacturers of these capsules are power consumption and size of the circuitry. Also, the system must be fast enough for real-time...
In this paper, we propose a new method for detecting hemorrhage areas and surgical instruments in robot-assisted laparoscopic surgery images. The proposed scheme utilizes CIELAB information to identify a region of interest (ROI) and segment it. Histogram equalization and Otsu's method are also adopted to compute the detection threshold. Detection is performed automatically and additional adjustment...
Colors play a fundamental role for children, both in the everyday life and in education. They recognize the surrounding world, and play games making a large use of colors. They learn letters and numbers by means of colors. As a consequence, early diagnosis of color blindness is an crucial to support an individual affected by this visual perception alteration at the initial phase of his/her life. The...
Diaper wearing elderly with functional impairments and/or incontinence is at high risk of contracting urinary tract infections. Nurses struggle with collection of urine samples for analysis. Therefore, a smartphone application is under development as a rapid screening device to work in conjunction with a colorimetric diaper assay that collects and tests urine within a diaper. The focus of this work...
This study presents a new algorithm to adaptively detect change points of functional connectivity networks in the brain. It uses scans from resting-state functional magnetic resonance imaging (rsfMRI) which is one of the major tools to investigate intrinsic brain functionality. Different regions of the resting brain form networks that change states within a few seconds to minutes. The change points...
Deep learning and unsupervised feature learning have received great attention in past years for their ability to transform input data into high level representations using machine learning techniques. Such interest has been growing steadily in the field of medical image diagnosis, particularly in melanoma classification. In this paper, a novel application of deep learning (stacked sparse auto-encoders)...
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