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1. CAUDLES-EF: Carotid Automated Ultrasound Double Line Extraction System Using Edge Flow

Author

Jasjit S. Suri, Andrew N. Nicolaides, Kristen M. Meiburger, Filippo Molinari, and Guang Zeng

Subjects
Adult, Male, Automated measurement, medicine.medical_specialty, Polyline distance, Lumen (anatomy), Risk Assessment, Standard deviation, Article, Pattern Recognition, Automated, Segmentation, Ultrasound, medicine, Image Processing, Computer-Assisted, Humans, Radiology, Nuclear Medicine and imaging, Multiresolution, Carotid imaging, Mathematics, Aged, Ultrasonography, Aged, 80 and over, Ground truth, Edge flow, Radiological and Ultrasound Technology, business.industry, Hausdorff distance, Intima-media thickness measurement, Middle Aged, Intima–media thickness, Computer Science Applications, Intensity (physics), Surgery, Carotid Arteries, Intima-media thickness, Cardiovascular Diseases, Connective Tissue, Localization, Line (geometry), Female, business, Tunica Intima, Carotid artery, Edge-flow operator, Algorithms, Biomedical engineering
Abstract

The evaluation of the carotid artery wall is essential for the diagnosis of cardiovascular pathologies or for the assessment of a patient’s cardiovascular risk. This paper presents a completely user-independent algorithm, which automatically extracts the far double line (lumen–intima and media–adventitia) in the carotid artery using an Edge Flow technique based on directional probability maps using the attributes of intensity and texture. Specifically, the algorithm traces the boundaries between the lumen and intima layer (line one) and between the media and adventitia layer (line two). The Carotid Automated Ultrasound Double Line Extraction System based on Edge-Flow (CAUDLES-EF) is characterized and validated by comparing the output of the algorithm with the manual tracing boundaries carried out by three experts. We also benchmark our new technique with the two other completely automatic techniques (CALEXia and CULEXsa) we previously published. Our multi-institutional database consisted of 300 longitudinal B-mode carotid images with normal and pathologic arteries. We compared our current new method with previous methods, and showed the mean and standard deviation for the three methods: CALEXia, CULEXsa, and CAUDLES-EF as 0.134 ± 0.088, 0.074 ± 0.092, and 0.043 ± 0.097 mm, respectively. Our IMT was slightly underestimated with respect to the ground truth IMT, but showed a uniform behavior over the entire database. Regarding the Figure of Merit (FoM), CALEXia and CULEXsa showed the values of 84.7% and 91.5%, respectively, while our new approach, CAUDLES-EF, performed the best at 94.8%, showing a good improvement compared to previous methods.

Published
2011

2. Optimistic chordal coloring: a coalescing heuristic for SSA form programs

Author

Brisk, Philip, Verma, Ajay K., and Ienne, Paolo

Subjects
Register Allocation, Coalescing, Performance, Chordal graphs, Improvements, Single Assignment Form, Software_PROGRAMMINGLANGUAGES, Computer Science::Data Structures and Algorithms, Computer Science::Numerical Analysis, Algorithms, Graph, MathematicsofComputing_DISCRETEMATHEMATICS, Time
Abstract

The interference graph for a procedure in Static Single Assignment (SSA) Form is chordal. Since the k-colorability problem can be solved in polynomial-time for chordal graphs, this result has generated interest in SSA-based heuristics for spilling and coalescing. Since copies can be folded during SSA construction, instances of the coalescing problem under SSA have fewer affinities than traditional methods. This paper presents Optimistic Chordal Coloring (OCC), a coalescing heuristic for chordal graphs. OCC was evaluated on interference graphs from embedded/multimedia benchmarks: in all cases, OCC found the optimal solution, and ran, on average, 2.30x faster than Iterated Register Coalescing.