Low-dose 2D X-ray angiography enhancement using 2-axis PCA for the preservation of blood-vessel region and noise minimization.
Enhancing 2D angiography while maintaining a low radiation dose has become an important research topic. However, it is difficult to enhance images while preserving vessel-structure details because X-ray noise and contrast blood vessels in 2D angiography have similar intensity distributions, which can lead to ambiguous images of vessel structures. In this paper, we propose a novel and fast vessel-enhancement method for 2D angiography. We apply filtering in the principal component analysis domain for vessel regions and background regions separately, using assumptions based on energy compaction. First, we identify an approximate vessel region using a Hessian-based method. Vessel and non-vessel regions are then represented sparsely by calculating their optimal bases separately. This is achieved by identifying periodic motion in the vessel region caused by the flow of the contrast medium through the blood vessels when viewed on the time axis. Finally, we obtain noise-free images by removing noise in the new coordinate domain for the optimal bases. Our method was validated for an X-ray system, using 10 low-dose sets for training and 20 low-dose sets for testing. The results were compared with those for a high-dose dataset with respect to noise-free images. The average enhancement rate was 93.11±0.71%. The average processing time for enhancing video comprising 50-70 frames was 0.80±0.35s, which is much faster than the previously proposed technique. Our method is applicable to 2D angiography procedures such as catheterization, which requires rapid and natural vessel enhancement.
Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea.
Yong Geun
YG
Lee
School of Computer Science & Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-Gu, Seoul 156-743, Republic of Korea.
Jeongjin
J
Lee
Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea.
Yeong-Gil
YG
Shin
Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea. Electronic address: hckang4cglab@gmail.com.
Ho Chul
HC
Kang
D015901:Angiography, Digital Subtraction / Q000379:methods* / Q000706:statistics & numerical data; D001808:Blood Vessels / Q000033:anatomy & histology; D003287:Contrast Media; D016208:Databases, Factual; D006801:Humans; D008491:Medical Informatics Applications; D025341:Principal Component Analysis; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement / Q000379:methods*; D059629:Signal-To-Noise Ratio
D003287:Contrast Media
2-Axis PCA; 2D angiography; Energy compaction; Noise reduction; Vessel enhancement; Vessel segmentation