Enhanced Dynamic Range X-ray Imaging
X-ray images can suffer from excess contrast. Often, image exposure is chosen to visually optimize the region of interest, but at the expense of over- and underexposed regions elsewhere in the image. When image values are interpreted quantitatively as projected absorption, both over- and underexposure leads to the loss of quantitative information. We propose to combine multiple exposures into a composite that uses only pixels from those exposures in which they are neither under- nor overexposed. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 24, 2017 Category: Bioinformatics Authors: Mark A. Haidekker, Logan Dain-kelley Morrison, Ajay Sharma, Emily Burke Source Type: research
A Generalized Active Shape Model for Segmentation of Liver in Low-contrast CT Volumes
To improve segmentation of normal/abnormal livers in contrast-enhanced/non-contrast CT image using the Active Shape Model (ASM) algorithm; we introduce a generalized profile model. We also intend to accurately detect boundary of liver where it touches nearby organs with similar intensities. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 23, 2017 Category: Bioinformatics Authors: Mina Esfandiarkhani, Amir Hossein Foruzan Source Type: research
Gap-Free Segmentation of Vascular Networks with Automatic Image Processing Pipeline
Current image processing techniques capture large vessels reliably but often fail to preserve connectivity in bifurcations and small vessels. Imaging artifacts and noise can create gaps and discontinuity of intensity that hinders segmentation of vascular trees. However, topological analysis of vascular trees require proper connectivity without gaps, loops or dangling segments. Proper tree connectivity is also important for high quality rendering of surface meshes for scientific visualization or 3D printing. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 20, 2017 Category: Bioinformatics Authors: Chih-Yang Hsu, Mahsa Ghaffari, Ali Alaraj, Michael Flannery, Xiaohong Joe Zhou, Andreas Linninger Source Type: research
Automatic detection and measurement of nuchal translucency
In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 19, 2017 Category: Bioinformatics Authors: Giuseppa Sciortino, Domenico Tegolo, Cesare Valenti Source Type: research
Comment on the paper “Network and Nakamura tridiagonal computational simulation of electrically-conducting biopolymer micro-morphic transport phenomena O. Anwar Bég, J. Zueco, M. Norouzi, M. Davoodi, A. A. Joneidi, Assma F. Elsayed, Computers in Biology and Medicine 44 (2014) 44–56”
The present comment concerns some doubtful results included in the above paper. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 17, 2017 Category: Bioinformatics Authors: Asterios Pantokratoras Tags: Short communication Source Type: research
Comment on the paper "Network and Nakamura tridiagonal computational simulation of electrically-conducting biopolymer micro-morphic transport phenomena O. Anwar B ég, J. Zueco, M. Norouzi, M. Davoodi, A. A. Joneidi, Assma F. Elsayed, Computers in Biology and Medicine 44 (2014) 44–56"
The present comment concerns some doubtful results included in the above paper. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 17, 2017 Category: Bioinformatics Authors: Asterios Pantokratoras Source Type: research
Bayesian Approach to Decompression Sickness Model Parameter Estimation
We examine both maximum likelihood and Bayesian approaches for estimating probabilistic decompression sickness model parameters. Maximum likelihood estimation treats parameters as fixed values and determines the best estimate through repeated trials, whereas the Bayesian approach treats parameters as random variables and determines the parameter probability distributions. We would ultimately like to know the probability that a parameter lies in a certain range rather than simply make statements about the repeatability of our estimator. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 16, 2017 Category: Bioinformatics Authors: L.E. Howle, P.W. Weber, J.M. Nichols Source Type: research
Spatial and Dynamical Handwriting Analysis in Mild Cognitive Impairment
This study was conducted as a first step towards the development of a diagnostic tool based on handwriting.Methods In this paper the handwriting sample of a group of 37 patients with MCI (mean age 76.1 ±5.8) and 37 healthy controls (mean age 74.8±5.7) was collected using a Livescribe Echo Pen while completing three tasks: (1) regular writing, (2) all-capital-letters writing, and (3) single letter multiply repeated. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 12, 2017 Category: Bioinformatics Authors: Jacek Kawa, Adam Bednorz, Paula St ępień, Jarosław Derejczyk, Monika Bugdol Source Type: research
Using discrete multi-physics for detailed exploration of hydrodynamics in an in vitro colon system
We developed a mathematical model that describes the motion of viscous fluids in the partially-filled colon caused by the periodic contractions of flexible walls (peristalsis). In-vitro data are used to validate the model. The model is then used to identify two fundamental mechanisms of mass transport: the surfing mode and the pouring mode. The first mechanism is faster, but only involves the surface of the liquid. The second mechanism causes deeper mixing, and appears to be the main transport mechanism. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 7, 2017 Category: Bioinformatics Authors: A. Alexiadis, K. Stamatopoulos, W. Wen, H.K. Batchelor, S. Bakalis, M. Barigou, M.J.H. Simmons Source Type: research
An Expert System for Selecting Wart Treatment Method
As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV) and may grow on all parts of body, especially hands and feet. There are several treatment methods for this illness. However, none of them can heal all patients. Consequently, physicians are looking for more effective and customized treatments for each patient. They are endeavoring to discover which treatments have better impacts on a particular patient. The aim of this study is to identify the appropriate treatment for two common types of warts (plantar and common) and to predict the responses of two of the best methods (immunotherapy and ...
Source: Computers in Biology and Medicine - January 5, 2017 Category: Bioinformatics Authors: Fahime Khozeimeh, Roohallah Alizadehsani, Mohamad Roshanzamir, Abbas Khosravi, Pouran Layegh, Saeid Nahavandi, Senior Member, IEEE Source Type: research
A computer-based simulator for intravascular photoacoustic images
Intravascular photoacoustic (IVPA) is a newly developed catheter-based imaging technique for the diagnosis of arterial atherosclerosis. A framework of simulating IVPA transversal images from a cross-sectional vessel model with given optical and acoustic parameters was presented. The light illumination and transportation in multi-layered wall and atherosclerotic plaque tissues were modeled through Monte Carlo (MC) simulation. The generation and transmission of photoacoustic (PA) waves in the acoustically homogeneous medium were modeled through the PA wave equation, which is solved explicitly with a finite difference time do...
Source: Computers in Biology and Medicine - January 5, 2017 Category: Bioinformatics Authors: Sun Zheng, Yuan Yuan, Han Duoduo Source Type: research
Modeling of the Photoplethysmogram During Atrial Fibrillation
A phenomenological model for simulating the photoplethysmogram (PPG) during atrial fibrillation (AF) is proposed. The simulated PPG is solely based on RR interval information, and, therefore, any annotated ECG database can be used to model sinus rhythm, AF, or rhythms with premature beats. A PPG pulse is modeled by a linear combination of a log-normal and two Gaussian waveforms. The model PPG is obtained by placing individual pulses according to the RR intervals so that a connected signal is created. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - December 27, 2016 Category: Bioinformatics Authors: Andrius Solo šenko, Andrius Petrėnas, Vaidotas Marozas, Leif Sörnmo Source Type: research
An Advanced MRI and MRSI Data Fusion Scheme for Enhancing Unsupervised Brain Tumor Differentiation
Proton Magnetic Resonance Spectroscopic Imaging (1H MRSI) has shown great potential in tumor diagnosis since it provides localized biochemical information discriminating different tissue types, though it typically has low spatial resolution. Magnetic Resonance Imaging (MRI) is widely used in tumor diagnosis as an in vivo tool due to its high resolution and excellent soft tissue discrimination. This paper presents an advanced data fusion scheme for brain tumor diagnosis using both MRSI and MRI data to improve the tumor differentiation accuracy of MRSI alone. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - December 25, 2016 Category: Bioinformatics Authors: Yuqian Li, Xin Liu, Feng Wei, Diana M. Sima, Sofie Van Cauter, Uwe Himmelreich, Yiming Pi, Guang Hu, Yi Yao, Sabine Van Huffel Source Type: research
A Comprehensive Non-invasive Framework for Diagnosing Prostate Cancer
Early detection of prostate cancer increases chances of patients' survival. Our automated non-invasive system for computer-aided diagnosis (CAD) of prostate cancer segments the prostate on diffusion-weighted magnetic resonance images (DW-MRI) acquired at different b-values, estimates its apparent diffusion coefficients (ADC), and classifies their descriptors – empirical cumulative distribution functions (CDF) – with a trained deep learning network. To segment the prostate, an evolving geometric (level-set-based) deformable model is guided by a speed function depending on intensity attributes extracted from the DW-MRI w...
Source: Computers in Biology and Medicine - December 21, 2016 Category: Bioinformatics Authors: Islam Reda, Ahmed Shalaby, Mohammed Elmogy, Ahmed Abou Elfotouh, Fahmi Khalifa, Mohamed Abou El-Ghar, Ehsan Hosseini-Asl, Georgy Gimel'farb, Naoufel Werghi, Ayman El-Baz Source Type: research
A Bayesian Model for Estimating Multi-State Disease Progression
A growing number of individuals who are considered at high risk of cancer are now routinely undergoing population screening. However, noted harms such as radiation exposure, overdiagnosis, and overtreatment underscore the need for better temporal models that predict who should be screened and at what frequency. The mean sojourn time (MST), an average duration period when a tumor can be detected by imaging but with no observable clinical symptoms, is a critical variable for formulating screening policy. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - December 21, 2016 Category: Bioinformatics Authors: Shiwen Shen, Simon X. Han, Panayiotis Petousis, Robert E. Weiss, Frank Meng, Alex A.T. Bui, Willliam Hsu Source Type: research
