Academic program models for undergraduate biomedical engineering.

There is a proliferation of medical devices across the globe for the diagnosis and therapy of diseases. Biomedical engineering (BME) plays a significant role in healthcare and advancing medical technologies thus creating a substantial demand for biomedical engineers at undergraduate and graduate levels. There has been a surge in undergraduate programs due to increasing demands from the biomedical industries to cover many of their segments from bench to bedside.

Editorial comment on Malkin and Keane (2010).

Malkin and Keane (Med Biol Eng Comput, 2010) take an innovative approach to determine if unused, broken medical and laboratory equipment could be repaired by volunteers with limited resources. Their positive results led them to suggest that resource-poor countries might benefit from an on-the-job educational program for local high school graduates. The program would train biomedical technician assistants (BTAs) who would repair medical devices and instrumentation and return them to service.

Incorporating temporal information into level set functional for robust ventricular boundary detection from echocardiographic image sequence.

Echocardiographic images often suffer from dropouts that lead to loss of signals on the ventricular boundary and cause the level set curve used to detect the boundary leaking out from the gaps on the boundary. In this paper, a novel method that incorporates temporal information into the level set functional is proposed to solve the leakage problem encountered when detecting the heart wall boundary from the echocardiographic image sequence. The ventricular boundary is quantitatively partitioned and classified into strong and weak segments.

Incorporating temporal information into active contour method for detecting heart wall boundary from echocardiographic image sequence.

A new method which incorporates temporal information into the active contour function is proposed to solve the dropout and speckle noise problems encountered when detecting the inner heart wall boundary from echocardiographic image sequence. The ventricular boundary is considered to be composed of strong and weak segments. The weak segments are interfered by image degradations in ultrasound, and they are too weak to constrain the curve evolution.

Watershed-presegmented snake for boundary detection and tracking of left ventricle in echocardiographic images.

In this paper, an automated method of boundary detection of the left ventricle (LV) is proposed. The method uses a watershed transform and morphological operation to locate the region containing the LV, then performs snake deformation with a multiscale directional edge map for the detection of the endocardial boundary of the LV.

Characteristic wave detection in ECG signal using morphological transform.

Background: Detection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG).

Methods: A multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative.

Life-threatening ventricular arrhythmia recognition by nonlinear descriptor.

Background: Ventricular tachycardia (VT) and ventricular fibrillation (VF) are ventricular cardiac arrhythmia that could be catastrophic and life threatening. Correct and timely detection of VT or VF can save lives.

Methods: In this paper, a multiscale-based non-linear descriptor, the Hurst index, is proposed to characterize the ECG episode, so that VT and VF can be recognized as different from normal sinus rhythm (NSR) in the descriptor domain.

Feature extraction for the analysis of colon status from the endoscopic images.

Background: Extracting features from the colonoscopic images is essential for getting the features, which characterizes the properties of the colon. The features are employed in the computer-assisted diagnosis of colonoscopic images to assist the physician in detecting the colon status.

Methods: Endoscopic images contain rich texture and color information.

Cardiac arrhythmia classification using autoregressive modeling.

Background: Computer-assisted arrhythmia recognition is critical for the management of cardiac disorders. Various techniques have been utilized to classify arrhythmias. Generally, these techniques classify two or three arrhythmias or have significantly large processing times.

ECG signal conditioning by morphological filtering.

Clinically obtained electrocardiographic (ECG) signals are often contaminated with different types of noise and baseline drifting commonly occurs. In order to facilitate automated ECG analysis, signal conditioning is undoubtedly a necessity. In this paper, a modified morphological filtering (MMF) technique is used for signal conditioning in order to accomplish baseline correction and noise suppression with minimum signal distortion.

Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter.

In this paper, the fitness of estimating vessel profiles with Gaussian function is evaluated and an amplitude-modified second-order Gaussian filter is proposed for the detection and measurement of vessels. Mathematical analysis is given and supported by a simulation and experiments to demonstrate that the vessel width can be measured in linear relationship with the "spreading factor" of the matched filter when the magnitude coefficient of the filter is suitably assigned. The absolute value of vessel diameter can be determined simply by using a precalibrated line, which is typically required since images are always system dependent.