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Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets
This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. Expand
Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database
We improve the concept of matched filtering, and propose a novel and accurate method for segmenting retinal blood vessel tree in high-resolution fundus images. Expand
Split-spectrum amplitude-decorrelation angiography with optical coherence tomography
Amplitude decorrelation measurement is sensitive to transverse flow and immune to phase noise in comparison to Doppler and other phase-based approaches. However, the high axial resolution of OCTExpand
Glaucoma risk index:  Automated glaucoma detection from color fundus images
We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. Expand
Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details
Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research. Expand
Robust Vessel Segmentation in Fundus Images
We present a method to reduce calculation time, achieve high accuracy, and increase sensitivity compared to the original Frangi method. Expand
Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye
Significance Retinal vascular diseases are a leading cause of blindness. Optical coherence tomography (OCT) has become the standard imaging modality for evaluating fluid accumulation in theseExpand
Quantitative Accuracy of Clinical 99mTc SPECT/CT Using Ordered-Subset Expectation Maximization with 3-Dimensional Resolution Recovery, Attenuation, and Scatter Correction
We present a calibration method of a clinical SPECT/CT device for quantitative 99mTc SPECT. We use a commercially available reconstruction package including ordered-subset expectation maximizationExpand
Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans
Robust and fast detection of anatomical structures is a prerequisite for both diagnostic and interventional medical image analysis. Expand
Unbiased and Mobile Gait Analysis Detects Motor Impairment in Parkinson's Disease
Motor impairments are the prerequisite for the diagnosis in Parkinson's disease (PD). The cardinal symptoms (bradykinesia, rigor, tremor, and postural instability) are used for disease staging andExpand