Search results for "artificial intelligence"

Unsupervised Numerical Characterization in Determining the Borders of Malignant Skin Tumors from Spectral Imagery

2021

For accurate removal of malignant skin tumors, it is crucial to assure the complete removal of the lesions. In the case of certain ill-defined tumors, it is clinically challenging to see the true borders of the tumor. In this paper, we introduce several computationally efficient approaches based on spectral imaging to guide clinicians in delineating tumor borders. First, we present algorithms that can be used effectively with simulated skin reflectance data. By using simulated data, we gain detailed information about the sensitivity of the different approaches and how variables defined by algorithms act in the skin model. Second, we demonstrate the performance of the algorithms with spectra…

ECG Analysis for Ventricular Fibrillation Detection Using a Boltzmann Network

2015

Arrhythmias consist on electrical alterations in the heart beat control. They can be identified by means of surface ECG leads. The main goal of this work is to provide a signal classification based on ECG signal waveform in the time-frequency domain especially targeted to Ventricular Fibrillation detection. The use of a classifier based on a Boltzmann network is proposed. However, a previous signal preprocessing is also required so that the Boltzmann network is fed with the appropriate data. In this case, an R-wave detector is used; after that, the Pseudo Wigner-Ville time-frequency distribution is obtained. This distribution is used to train and test the network, which handles it as an ima…

Stereoscopic Viewing Enhances Visually Induced Motion Sickness but Sound Does Not

2012

Optic flow in visual displays or virtual environments often induces motion sickness (MS). We conducted two studies to analyze the effects of stereopsis, background sound, and realism (video vs. simulation) on the severity of MS and related feelings of immersion and vection. In Experiment 1, 79 participants watched either a 15-min-long video clip taken during a real roller coaster ride, or a precise simulation of the same ride. Additionally, half of the participants watched the movie in 2D, and the other half in 3D. MS was measured using the Simulator Sickness Questionnaire (SSQ) and the Fast Motion Sickness Scale (FMS). Results showed a significant interaction for both variables, indicatin…

Smartphone single-snapshot mapping of skin chromophores

2016

Suitability of smartphone for single-snapshot mapping of skin melanin, oxy-hemoglobin and deoxy-hemoglobin under 3-wavelengths illumination was demonstrated. Simultaneous 448-532-659 nm illumination was provided by a portable laser-based prototype.

Letter: Image-Guided Navigation and Robotics in Spine Surgery.

2020

Prostate Cancer Segmentation from Multiparametric MRI Based on Fuzzy Bayesian Model

2014

International audience

Photoaging evaluation by RGB images using a smartphone for photodynamic therapy assessment

2017

In this study was evaluated the photoaging of patients' skins by the processing of RGB images acquired with an optical system based on a smartphone. Two groups were approached: a younger and an older.

Validation of Knee KL-classifying Deep Neural Network with Finnish Patient Data

2021

Osteoarthritis (OA) is the most common form of joint disease in the world. The diagnosis of OA is currently made by human experts and suffers from subjectivity, but recently new promising detection algorithms have been developed. We validated the current state-of-the-art KL-classifying neural network model for knee OA using knee X-rays taken from postmenopausal women suffering from knee pain attributable to OA. The performance of the model on the clinical data was considerably lower compared to the previous results on population-based test data. This suggests that the performance of the current grading methods is not yet adequate to be applied in clinical settings. The present results also …

Modelling cardiac mechanics of left ventricular noncompaction

2020

Left ventricular noncompaction (LVNC) can be defined as a cardiomyopathy characterised by a pattern of prominent trabecular structure and deep intertrabecular recesses, that is thought to be caused by an arrest of normal endomyocardial morphogenesis. Using patient-specific computational modelling, we assessed the cardiac mechanics of five patients with LVNC and compared myocardial stress and pump performance to those of healthy controls. Findings shown that patients with LVNC have impaired left ventricular (LV) function, making it possible that the lack of fibre shortening of noncompacted layer can determine poor heart function. Pronounced end-systolic wall stress on left ventricular wall o…

Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network

2018

In this study we apply 3D convolutional neural network (CNN) for tree species identification. Study includes the three most common Finnish tree species. Study uses a relatively large high-resolution spectral data set, which contains also a digital surface model for the trees. Data has been gathered using an unmanned aerial vehicle, a framing hyperspectral imager and a regular RGB camera. Achieved classification results are promising by with overall accuracy of 96.2 % for the classification of the validation data set. nonPeerReviewed