The vectorial basis of patches (left) learnt from a high quality tomographic reconstruction of the phase image of a human breast(right).

<p>In each atom of the dictionary the upper part is the component while the lower part is the component.</p

Results from the numerical experiment on the Lena image .

<p>The sinogram is obtained by projecting the image at 80 angles between 0 and 180 degree. A comparison of the images reconstructed with the FBP (a), the EST (b), the algorithm (c), and our DL method (d) is shown. The final image (e) is the same cropped zone in the original image for the sake of comparison (e).</p

The objective functions and (floating solution form) versus iteration number for FISTA optimisation.

<p>The objective functions and (floating solution form) versus iteration number for FISTA optimisation.</p

The quality improvement factor versus the regularisation parameter (squares) for our overlapping patches method, and versus (dots) for the total variation method.

<p>The used phantom is the image of Lena, the reconstruction is performed using only noised projections. For our method we have used a value fixed to , the patches basis shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114325#pone-0114325-g001" target="_blank">figure 1</a> and a step size of .</p

Reconstruction of a computed tomographic slice of the breast.

<p>The images on the first and second row are the X and Y phase gradients, respectively. In the left column the results of the reconstruction obtained with the FBP method using the full set of data are reported. In the right column the results of our method using one projection over five are shown. For these reconstructions we set and .</p

Comparison of the tomographic image reconstructions of the breast obtained with the FBP (b and g), the TV minimization (c and h), the EST (d and i), and our method (e and j) using 200 projections over the 1000 available.

<p>The right images (f and k) are the images computed with the FBP using the entire set of projections. The top image (a) is the result obtained by the FBP using the entire set of projections. It is reported for showing the location of the insets. The SSIM values are reported based on the FBP full dose image.</p

Results from the numerical experiment on the Lena image with additive Poisson noise.

<p>The sinogram is obtained by projecting the image at 80 angles between 0 and 180 degree, and adding a Poisson noise with a standard deviation equal to 0.3% of the maximal sinogram value. A comparison of the images reconstructed with the FBP (a), the EST (b), the algorithm (c), and our DL method (d) is shown. The final image (e) is the same cropped zone in the original image for the sake of comparison (e).</p

The training image used in our work (a) and the dictionary elements obtained by using the K-SVD algorithm (b).

<p>This basis is then used for the numerical experiment.</p

Bredia hirsuta Bl.

原著和名: ハシカンボク科名: ノボタン科 = Melastomataceae採集地: 鹿児島県 屋久島 屋久町 安房〜上屋久町 小杉谷 (大隅 屋久島 安房〜小杉谷)採集日: 1964/8/18採集者: 萩庭丈壽整理番号: JH045335国立科学博物館整理番号: TNS-VS-99533

Clinical mammography and sonography of patient B.

<p>In-vivo mammography in mediolateral oblique projection before (A), after 4 cycles NAC (B) and after completion of NAC (C). Ultrasound before NAC (D). Tumor indicated by arrowheads. Please note the excessive calcifications (white spots in A–D) within the tumor. The exact tumor borders are not visible in mammography and sonography.</p