Ian Chan

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A multichannel statistical classifier for detecting prostate cancer was developed and validated by combining information from three different magnetic resonance (MR) methodologies: T2-weighted, T2-mapping, and line scan diffusion imaging (LSDI). From these MR sequences, four different sets of image intensities were obtained: T2-weighted (T2W) from(More)
Accurate estimation of ventricular volumes plays an essential role in clinical diagnosis of cardiac diseases. Existing methods either rely on segmentation or are restricted to direct estimation of the left ventricle. In this paper, we propose a novel method for direct and joint volume estimation of bi-ventricles, i.e., the left and right ventricles, without(More)
Direct estimation of cardiac ventricular volumes has become increasingly popular and important in cardiac function analysis due to its effectiveness and efficiency by avoiding an intermediate segmentation step. However, existing methods rely on either intensive user inputs or problematic assumptions. To realize the full capacities of direct estimation, this(More)
Ballistic conductance fluctuations were measured in a GaAs quantum dot as a function of shape distortion and magnetic field. Shape distortion provides a novel source of conductance fluctuations and creates an effective " ensemble of dots, " allowing statistics to be studied at fixed field. Continuous changes in fluctuation statistics due to breaking of(More)
Cardiac four-chamber volume estimation serves as a fundamental and crucial role in clinical quantitative analysis of whole heart functions. It is a challenging task due to the huge complexity of the four chambers including great appearance variations, huge shape deformation and interference between chambers. Direct estimation has recently emerged as an(More)
The diagnosis, comparative and population study of cardiac radiology data require heart segmentation on increasingly large amount of images from different modalities/chambers/patients under various imaging views. Most existing automatic cardiac segmentation methods are often limited to single image segmentation with regulated modality/region settings or(More)
Image-based diagnosis and population study on cardiac problems require automatic segmentation on increasingly large amount of data from different protocols, different views, and different patients. However , current algorithms are often limited to regulated settings such as fixed view and single image from one specific modality, where the supervised(More)