Noise power spectrum and modulation transfer function analysis of breast tomosynthesis imaging

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1 Noise power spectrum and modulation transfer function analysis of breast tomosynthesis imaging Weihua Zhou a, Linlin Cong b, Xin Qian c, Yueh Z. Lee d, Jianping Lu c,e, Otto Zhou c,e, *Ying Chen a,b a Dept. of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL62901; b Biomedical Engineering Graduate Program, Southern Illinois University, Carbondale, IL 62901; c Dept. of Physics and Astronomy, and Curriculum in Applied Sciences and Engineering, The University of North Carolina, Chapel Hill, NC 27599; d Dept. of Radiology, The University of North Carolina, Chapel Hill, NC 27599; e Lineberger Comprehensive Cancer Center, The University of North Carolina, Chapel Hill, NC * Corresponding author The recent commercialization of digital breast tomosynthesis systems realizes the clinical applications of this novel three-dimensional imaging technology. The total dosage of breast tomosynthesis for single patient is comparable to that of the traditional mammography. This paper presents our continuous work on image quality analysis for the optimization of a new multi-beam breast tomosynthesis system based on carbon nanotube X-ray emission technology. Several tomosynthesis reconstruction algorithms were implemented to reconstruct the phantom data. Noise power spectrum and modulation transfer function were investigated to evaluate the image quality. Keywords: digital breast tomosynthesis (DBT), noise power spectrum (NPS), modulation transfer function (MTF), back projection (BP), filtered back-projection (FBP) I Introduction Breast tomosynthesis imaging improves early breast cancer detection by providing three-dimensional information of the breast object [1-3]. It acquires a few limited-angle projection images and then reconstructs the internal structures of the object. Compared to mammography, this technology overcomes the ambiguities caused by overlapping tissues. The total dosage is comparable to that of the traditional mammography [1]. It is promising to challenge the current mammography screening routine [3, 4]. A lot of attentions from both academia and manufactures have been accumulated to digital breast tomosynthesis technology. In USA, FDA has issued its approval to Hologic s DBT system [5]. Breast tomosynthesis has been used for screening in Massachusetts General Hospital [6] V. 1 (p.1 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

2 The current DBT prototype systems reutilize the design of traditional mammography system in which the X-ray tube rotates along a partial iso-centric arc path. It has the advantages of decreasing the cost of system upgrade and operators training, but the motion blur may reduce the image quality [7]. A parallel multi-beam digital breast tomosynthesis system, invented by Zhou et al [8-10], has great potentials to remove the motion blur. It adopts carbon-nano tubes as X-ray emitters, fixes multiple X-ray tubes along the line which is parallel to the detector surface, and controls the emission of the X-ray signal by an electronic switch. This design eliminates the motion blur caused by the rotation of the X-ray tube in the current commercially available digital breast tomosynthesis systems. It can also decrease the total time of acquiring projection images, thereafter reduces the awaiting time of patients. In SPIE 2009 and 2010 [7, 11, 12 ], we reported our preliminary results of image reconstruction and image quality investigation with the multi-beam breast tomosynthesis system. The investigations suggested that this new system is capable of providing three-dimensional internal structural distribution of objects. Evaluation based on image quality analysis in spatial domain showed that different image reconstruction algorithms and imaging configurations can influence the system performance. It has been demonstrated that frequency-domain based image quality measurement methodologies have a lot of advantages [13, 14]. Since real object can be decomposed into sine waves with different amplitudes, frequencies and phases, frequency domain methods are flexible to predict the system response by single analysis [13]. MTF (f) and NPS (f) are frequently selected as the merits to characterize the performance of medical systems [15, 16]. This paper presents our work on further investigation of image quality with the new multi-beam DBT prototype system. Both noise power spectrum (NPS) and modulation transfer function (MTF) were evaluated for several representative reconstruction algorithms and imaging configurations. II Material and Methods A new DBT prototype system was built up by our collaborators [8, 10]. The system has 31 X-ray beam sources evenly distributed with 1 0 separations. A digital flat-panel detector with the pixel pitch of 140 um was integrated into the prototype system. The image size is The total exposure level was 80 mas. Figure 1 shows the parallel imaging geometry of the investigated breast tomosynthesis imaging system. The X-ray tubes are aligned along Y direction. The distance from X-ray source plane to the detector plane (SID) is mm V. 1 (p.2 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

3 X-ray Tubes 1 0 z x SID y θ O Object Detector (b) Figure 1. Parallel breast tomosynthesis imaging geometry. Two representative image reconstruction algorithms, including back projection (BP) [17] and filtered back projection (FBP) [18-20], were investigated in this paper. BP algorithm calculates the shift amount of each pixel on the reconstructed planes to reconstruct the object. FBP applies filters to reduce out-of-plane artifacts. An investigation about the noise and signal propagation of FBP with a flat panel partial isocentric DBT system was reported by Zhao et. al. [20]. Our implementation uses four filters: ramp filter, Hanning filter, slice profile filter, Gaussian filter [19, 21]. Gaussian filter is a low-pass filter which is intended to suppress the noise. It changes the appearance of high-frequency components. In this paper, we investigated FBP algorithm with two versions: full version with all above four filters was called as FBP ; a version without Gaussian filter was called as FBP_nogaussian. A. Measurement of NPS(f) For NPS analysis, noise propagation was investigated by acquiring the projection images of a breast tissue equivalent phantom with the DBT prototype system. In order to mimic the equivalent distribution of attenuation and scatter radiation in breast tissues, the phantom, 40 mm thick, was placed on the surface cover of the detector. For each reconstruction algorithm, all the slice images with 1 mm plane spacing were reconstructed to cover the entire breast phantom. In NPS calculation [2, 14], regions of interest (ROIs) with the size of pixels were cut from the reconstructed planes at the same height above the detector. Each ROI was evenly divided into 8 blocks with a size of pixels. For each block, a line curve fitting through the ensemble-averaged NPS estimate was used to obtain an approximation to the greatest slope of the true NPS. Finally, we extracted the frequency components from each block and formed the smoothened NPS curves. B. Measurement of MTF(f) V. 1 (p.3 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

4 The modulation transform function can be divided into two parts [2, 14]. One is the projection MTF, ProjMTF(f), and it comes from the imaging system. Generally it is used to evaluate the hardware including the X-ray focal spot and detector. The conventional MTF measurement can be transplanted to investigate projection MTF. The another MTF component is reconstruction MTF (ReconMTF(f)). It characterizes signal propagation in different reconstruction models and imaging configurations, for example, view angular range and number of projection images. In this paper we tested ReconMTF(f). In our ReconMTF(f) measurement, 9 impulses, evenly located inside one pixel, were computer simulated with the imaging configuration of the prototype system. Figure 2 shows the impulse locations inside the pixel. All the impulses were placed in a plane that is 45.0 mm above the detector. Ray-tracing method was used to generate the projection images [2]. The images were then reconstructed P 1 P 2 P P 4 P 5 P P 7 P 8 P 9 Figure 2. Locations of simulated impulses for ReconMTF(f) measurement. In ReconMTF(f) calculation, the reconstructed slices were selected and Fourier transform of the reconstruction planes were calculated to extract frequency components and form the MTF curves. Two groups of ReconMTF(f) were reported: (1) the ReconMTF(f) when total view angle ranges and number of projection image change; (2) the ReconMTF(f) on the planes with different Z distances. III Results A. Results of NPS (f) Measurement NPS curves along both X and Y directions with the parallel imaging configuration and different reconstruction algorithms were shown in Figure 3. In X direction (Figure 3(c) and 3(e)), two FBP versions have the similar appearances. In Y direction (Figure 3(b), 3(d), and 3(f) ), the full-version FBP shows high-frequency drop-off compared to FBP_nogaussian due to applied Gaussian filter V. 1 (p.4 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

5 (a) (b) (c) (d) (e) Figure 3. NPS curves of the parallel DBT prototype system. (a) X direction of BP. (b) Y direction of BP. (c) X direction of FBP. (d) Y direction of FBP. (e) X direction of FBP_nogaussian. (f) Y direction of FBP_nogaussian. (f) V. 1 (p.5 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

6 B. Results of MTF(f) Measurement Figure 4 shows the ReconMTF(f) with different view angle (VA) ranges and number of projection image (Proj). There is no obvious difference in BP. In two FBP versions, the four imaging configurations were clustered into three groups. (a) (b) (c) Figure 4. Reconstruction MTF curves with different imaging configurations and reconstruction algorithms. (a) BP. (b) FBP. (c) FBP_nogaussian. Figure 5 shows the ReconMTF(f) on different reconstructed planes. The in-plane location is 45.0 mm above the detector. + means the Z distance is higher than the in-plane distance. As shown in Figure 5, when the plane is farther away from the plane where the impulse is, ReconMTF(f) decreases V. 1 (p.6 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

7 (a) (b) (c) Figure 5. Reconstruction MTF curves with different imaging configuration and reconstruction algorithms. (a) BP. (b) FBP. (c) FBP_nogaussian. IV Conclusions This work presents our continuous effort to optimize the tomosynthesis imaging configuration and reconstruction algorithms with a novel nanotechnology enabled multi-beam DBT prototype system. Image quality analysis of MTF and NPS is essential to evaluate the signal and noise properties. Physical measurements and computer simulations were performed in this paper to evaluate image quality for the new parallel imaging system and representative algorithms. Results showed that the MTF and NPS analysis on the reconstructed plane can be used to serve as the foundations for the optimization of imaging configurations and reconstruction for breast tomosynthesis imaging V. 1 (p.7 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

8 Acknowledgement This work is supported by NIH/NCI R01 CA A1. We acknowledge Jian Fang and Shiyu Xu at the Biomedical Imaging Lab of Southern Illinois University Carbondale for data collection and related work. We appreciate Andrew Tucker at North Carolina State University for his kind help of acquiring tomosynthesis datasets. REFERENCE [1] Dobbins, J.T., Godfrey, D.J., Digital X-ray tomosynthesis: current state of the art and clinical potential, Phys. Med. Biol. 48, (2003). [2] Chen, Y., Digital breast tomosynthesis (DBT) - a novel imaging technology to improve early breast cancer detection: implementation, comparison and optimization, Ph.D. dissertation, Duke University (2007). [3] Chen, Y., Breast Tomosynthesis, book chapter, in Physics of Mammographic Imaging, ed. M. Markey, Taylor & Francis, 2011(Accepted). [4] Park, J.M., Franken, E.A., Garg, M., Fajardo, L.L., Niklason, L.T., Breast tomosynthesis: present considerations and future applications, Radiographics. 2007;27(Suppl 1): S (2007). [5] Hologic Inc. "Hologic Receives FDA Approval for First 3-D Digital Mammography (Breast Tomosynthesis) System". Accessed on December 20, [6] Massachusetts General Hospital. "Massachusetts General Hospital is first in the nation to do mammography screening using 3D breast tomosynthesis". Accessed on December 20, [7] Chen, Y., Zhou, W., Yang, G., Lu, J.P., and Zhou, O., Breast tomosynthesis reconstruction with a multi-beam x-ray source, Proc. SPIE 7258, (2009). [8] Zhang, J., Yang, G., Lu, J.P., Zhou, O., Multiplexing radiography using a carbon nanotube based x-ray source, Applied Physics Letter 89, (2006). [9] Lalush, D.S., Quan, E., Rajaram, R., Zhang, J., Lu, J.P., Zhou, O., Tomosynthesis reconstruction from multi-beam x-ray sources, Proceedings of 2006 IEEE International Symposium on Biomedical Imaging, (2006). [10] Yang, G., Rajaram, Cao, G., Sultana, S., Liu, Z., Lalush, D., Lu, J.P., Zhou, O., Stationary digital breast tomosynthesis system with a multi-beam field emission x-ray source array, Proc. SPIE 6913, 69131A (2008). [11] Zhou, W., Xin, Q., Lu, J.P., Zhou, O., Chen, Y., Multi-beam X-ray source breast tomosynthesis reconstruction with different algorithms, Proc. SPIE, 7622H.1-8 (2010). [12] Balla, A., Zhou, W., Chen, Y., Impulse Response Characterization of Breast Tomosynthesis Reconstruction with Parallel Imaging Configurations, Proc. SPIE, 76225K.1-8 (2010) V. 1 (p.8 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM

9 [13] Nishikawa, R.M., "The fundamentals of MTF, Wiener spectra, and DQE". Accessed on September 28, [14] Chen, Y., Zhou, W., Dobbins, J.T., Fourier-Domain Methods for Optimization of Tomosynthesis (NEQ), book chapter, in Tomosynthesis Imaging, ed. I. Reiser and S. Glick, Taylor & Francis, (2011) (Accepted). [15] Samei, E., Ranger, N.T., Dobbins, J.T., Chen, Y., "Intercomparison of methods for image quality characterization. I. Modulation transfer function". Med. Phys. 33(5): (2006). [16] Dobbins, J.T., Samei, E., Ranger, N.T., Chen, Y., "Intercomparison of methods for image quality characterization. II. Noise power spectrum. Med. Phys. 33(5): (2006). [17] Chen, Y., Lo, J.Y., Dobbins, J.T., Importance of point-by-point back projection (BP) correction for isocentric motion in digital breast tomosynthesis: Relevance to morphology of microcalcifications, Med. Phys. 34(10), (2007). [18] Mertelemeier, T., Orman, J., Haerer, W., Dudam, M.K., Optimizing filtered backprojection reconstruction for a breast tomosynthesis prototype device, Proc. SPIE 6142, (2006). [19] Lauritsch, G. and Haerer, W., A theoretical framework for filtered back-projection in tomosynthesis, Proc. SPIE 3338, (1998). [20] Zhao, B., Zhao, W., "Three-dimensional linear system analysis for breast tomosynthesis". Med. Phys. 35(12): (2008). [21] Cong, L., Zhou, W., Chen, Y., Effects of slice thickness filter in filtered backprojection reconstruction with parallel breast tomosynthesis imaging configuration, Proc. IEEE-International Symposium on Intelligent Biological Medicine(2011) V. 1 (p.9 of 9) / Color: No / Format: Letter / Date: 1/11/2013 5:14:26 PM