FUJIFILM Mammography Image Solutions

FatMammary gland

Contrast variation: large Contrast variation: small

FatMammarygland

Contrast

Tran

sit

dose

FatMammarygland

Contrast

Tran

sit

dose

FatMammarygland

Contrast

Tran

sit

dose

FatMammarygland

Contrast

Tran

sit

dose

Mammary gland:thin

X-ray attenuation: low X-ray attenuation: high

W anode Mo anode W anode Mo anode

Mammary gland:thickFatMammary gland

Normal dose 30% less dose

Dynamic Visualization + u gradation

(ACM processing)

ISCMo anode W anode

+ ISC

2DFSC

MFP + T (hard copy) gradation

W (soft copy) gradation

Standard components

� Exposure stand (FDR-3500DRLH):

Approx. 624 (W) � 1270 (D) � 1974 (H) mm / Approx. 370kg / AC 200/208/220/230/240V • Control cabinet: Approx. 503 (W) � 205 (D) � 530 (H)mm / Approx. 20kg • Generator: Approx. 445 (W) � 315 (D) � 825 (H)mm / Approx. 70kg� AWS (FDR-3000AWS): Approx. 700 (W) � 420 (D) � 1900 (H)mm / Approx. 90kg

(including protective shield and operation table) / Main unit: AC 100-240V

Main specifications

Correction of spectrum conversion and

scattered radiation

FUJIFILM developed image processing technology Excellent-m using artificial intelligence technology that acknowledges subject structure more accurately by utilizing the knowledge accumulated over many years of X-ray imaging and diagnosis. Excellent-m can provide highly sharp mammography images under low-dose exposure contributing to comfortable mammography screenings for recipients and healthcare professionals.

ISC – OFF ISC – ON

Mechanisms of image-based spectrum conversion

ISC Image-based Spectrum Conversion Optimization of contrast variations caused by differences in radiation quality

Subject information is recognized by image analysis, correcting the variations in image contrast caused by differences in amount and compressed thickness of mammary glands and fat, and X-ray spectrum. Although the images are taken with a W anode, contrast comparable to those with a Mo anode is successfully achieved.

Contrast variations can be optimized by correcting the contrast ratios based on the difference between W and Mo anodes per amount of mammary gland / fat or thickness of the breast.

Exposure conditions, breast thicknessProperties of X-ray absorption in tissue

Measurement of contrast

Conversion of contrast

Images comparable with Mo tube

High definition images with 50 µm pixel size, allowing exposure with 30% dose reduction*2

+

S-View

3D

ISR

Iterative Super-Resolution (ISR) reconstruction • Super-resolution technology• Iterative reconstruction (artifact suppression / noise reduction)

Image-based Spectrum Conversion (ISC)

Fine Structure Control (FSC)

Mammography Image Processing Profiles

FUJIFILM has pursued higher image quality and lower X-ray dose for mammography equipment by making full use of image processing technology. Through advanced technological innovations, we continuously endeavor to bring our mammography equipment to a higher level in terms of image quality and dose reduction.

TomosynthesisReconstruction

Continuous challenges to higher image quality and lower X-ray dose through image processing technology.

Ref. No. XB-1046E (SK·17·02·F1079·F9711) Printed in Japan ©2017 FUJIFILM Corporation2-26-30, Nishiazabu, Minato-ku, Tokyo 106-8620, Japan.

The appearance and specifications may be subject to change.

FUJIFILM supports the Pink Ribbon Campaignfor early detection of breast cancer

FSC analyzes exposured images using artificial intelligence technology. This technology offers high quality images by allowing proper recognition of breast structure patterns and optimizing sharpness and contrast of fine structures (such as mammary gland and calcification) important for mammography interpretation. Simultaneously, noise supression is added to enable low-dose exposure.

Structure pattern recognition processing

FSC Fine Structure Control

Flow of FSC processing

Reduction of noise to sharpen fine structure in the breast

FSC (30% reduction in dose)Conventional processing (30% reduction in dose)

Conventional processing

Exposure Structure pattern recognition

Sharpness/contrast improvement

Images with improved sharpness/contrast

Using the information on mammary glands and calcification contained in images, FSC recognizes complicated structural patterns in each pixel such as straight, curved and intersecting lines that are created with locally populated similar pixel values. Based on the information of the recognized struc-tural patterns, sharpness/contrast is improved for normal structures and lesions of the subject, while it prevents noise from increasing by decreasing the information in which random pixel values are locally populated. Structure pattern recognition is executed with a technology to recognize structures closer to those of the human body.

PC

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4C 色数297mm×615mm

サイズ

受注番号

21 -3374265

得意先名

富士フイルムビジネス

エキスパート㈱様

品　　　名

マンモ画像処理

カタログ(

英語)

12/21大類

00/00■■■

00/00■■■

00/00■■■

日付・作業担当者

１

２

４

３

作業ＭＡＣ

280進行担当

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表面

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Fig. 1: Phantom images simulating calcification

Collecting images from different angles

Conventional method Super-resolution techniques

(a) Without super-resolution (b) With super-resolution

Mechanisms of super-resolution technology Frequency response (direction of tube movement)

Shar

pnes

s Withuper-resolution

Withoutsuper-resolution

Coarse Structure Fine Structure

Super-resolution technology

100 µm

100

µm

100 µm

100

µm

*1: A series of basic technologies to make a computer have a human-like intelligence. We employ an image recognition technology utilized for artificial intelligence in processing of the X-rays images.*2: Based on the comparison to our previous images acquired by the conventional method.

High quality images using unique iterative super-resolution (ISR) reconstruction, enabling 40% dose reduction*2 with 3D.

[FBP method] The path of X-ray that penetrates through a subject and reaches the detector is spatially tracked back toward the X-ray source for each pixel in the detector, positioning each projected image based on the slice height and adding pixel values of projected images to generate a sliced image of the subject.

[Problems] Since the projection angle of tomosynthesis is limited, complete regeneration of a sliced image is impossible in principle, and structures out of the focal plane appear on the sliced image as an artifact. This artifact could reduce the contrast between mammary glands and tumor masses. Therefore, additional effort in interpretation becomes necessary, such as estimating density information while referring to conventional mammography images.1)

Tomosynthesis reconstruction by conventional (FBP) method and its problems

Super-resolution is a high-resolution technology in which multiple observed images with slightly different information allow for the acquisition of images with finer spatial sampling interval.2, 3)

Some images captured from slightly different directions are aligned with finer accuracy than the spatial sampling interval of observed images, and are plotted on the same space. On this space, if pixel grids are determined at finer intervals than the pixel pitch of the detector, information will be con-tained in the grids; and thus, information that cannot be acquired by simple interpolation can be restored. Fig. 1 shows the difference in an example of phantom images that simulate calcification. The method that uses super-resolution (b) significantly improved the visibility and depiction of the shape of calcification.

Super-resolution technology

Beyond the physical limitations of the exposure equipment, ISR can generate higher-resolution images compared to the originally observed images and bring out images with high sharpness through restoration of fine structures.

Super-resolution requires high-precision alignment, in which displace-ment in projection processing is accurately considered for each pixel.

Each pixel in a projected image has different information

Each pixel in a projected image is slightly displaced

ISR Iterative Super-Resolution reconstruction

Generation of low-dose and high quality tomosynthesis images by iterative reconstruction and super-resolution techniques

+ With recognition technology utilized for artificial intelligence, ISR can estimate the three-dimensional structure of a subject by repeatedly comparing projected images with sliced images and excluding the patterns that are not part of human body structure.

Iterative reconstruction

(1) Artifact suppression (2) Noise reduction

Transition to mammography that can provide high quality images with low-doseExcellent-m, image processing using artificial intelligence (AI) technology*1

FatMammary gland

Contrast variation: large Contrast variation: small

FatMammarygland

Contrast

Tran

sit

dose

FatMammarygland

Contrast

Tran

sit

dose

FatMammarygland

Contrast

Tran

sit

dose

FatMammarygland

Contrast

Tran

sit

dose

Mammary gland:thin

X-ray attenuation: low X-ray attenuation: high

W anode Mo anode W anode Mo anode

Mammary gland:thickFatMammary gland

FUJIFILM developed image processing technology Excellent-m using artificial intelligence technology that acknowledges subject structure more accurately by utilizing the knowledge accumulated over many years of X-ray imaging and diagnosis. Excellent-m can provide highly sharp mammography images under low-dose exposure contributing to comfortable mammography screenings for recipients and healthcare professionals.

ISC – OFF ISC – ON

Mechanisms of image-based spectrum conversion

ISC Image-based Spectrum Conversion Optimization of contrast variations caused by differences in radiation quality

Subject information is recognized by image analysis, correcting the variations in image contrast caused by differences in amount and compressed thickness of mammary glands and fat, and X-ray spectrum. Although the images are taken with a W anode, contrast comparable to those with a Mo anode is successfully achieved.

Contrast variations can be optimized by correcting the contrast ratios based on the difference between W and Mo anodes per amount of mammary gland / fat or thickness of the breast.

Exposure conditions, breast thicknessProperties of X-ray absorption in tissue

Measurement of contrast

Conversion of contrast

Images comparable with Mo tube

High definition images with 50 µm pixel size, allowing exposure with 30% dose reduction*2

+

FSC analyzes exposed images using artificial intelligence technology. This technology offers high quality images by allowing proper recognition of breast structure patterns and optimizing sharpness and contrast of fine structures (such as mammary gland and calcification) important for mammography interpretation. Simultaneously, noise suppression is added to enable low-dose exposure.

Structure pattern recognition processing

FSC Fine Structure Control

Flow of FSC processing

Reduction of noise to sharpen fine structure in the breast

FSC (30% reduction in dose)Conventional processing (30% reduction in dose)

Conventional processing

Exposure Structure pattern recognition

Sharpness/contrast improvement

Images with improved sharpness/contrast

Using the information on mammary glands and calcification contained in images, FSC recognizes complicated structural patterns in each pixel such as straight, curved and intersecting lines that are created with locally populated similar pixel values. Based on the information of the recognized struc-tural patterns, sharpness/contrast is improved for normal structures and lesions of the subject, while it prevents noise from increasing by decreasing the information in which random pixel values are locally populated. Structure pattern recognition is executed with a technology to recognize structures closer to those of the human body.

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FBP method

(a) FBP

Fig. 3: Improved granularity with a filter

Fig. 4: Effects of improved granularity

(b) ISR

ISR method (40% reduction in dose)

HR-mode

3.5 mm

2.7 mm

0 mm(Focal plane)

-5 mm

-10 mm

Reconstruction method

Out of focal plane

Focal Plane

FBP reconstruction ISR reconstruction

Calcification

Artifact due to calcification

(a) High-contrast subject

-3 mm-5 mm -0 mm +3 mm +5 mm -10 mm -5 mm 0 mm +5 mm +10 mm

(b) Low-contrast subject

References

PMMA 20 mm

CDMAM phantom

FBPISR

FBPISR

40% dosereduction

(ISR)

Fig. 2: Effects of iterative reconstruction

FBPreconstruction

ISRreconstruction

Z-resolution

Mea

n sq

uare

d er

ror

5 10 15 20 250

Distance from focal plane (mm)

Fig. 1: Phantom images simulating calcification

Collecting images from different angles

Conventional method Super-resolution techniques

(a) Without super-resolution (b) With super-resolution

Mechanisms of super-resolution technology Frequency response (direction of tube movement)

Shar

pnes

s Withuper-resolution

Withoutsuper-resolution

Coarse Structure Fine Structure

Super-resolution technology

100 µm

100

µm

100 µm

100

µm

Thre

shol

d go

ld t

hick

ness

(um

)

10

1

0.1 1Detail Diameter (mm)

Thre

shol

d go

ld t

hick

ness

(um

)

10

1

0.1 1Detail Diameter (mm)

Filter control by pattern recognition

ST-mode

9.5 mm

7.7 mm

FBP

ISR

Fig. 7: Images of a CDMAM phantom

*1: A series of basic technologies to make a computer have a human-like intelligence. We employ an image recognition technology utilized for artificial intelligence in processing of the X-rays images.*2: Based on the comparison to our previous images acquired by the conventional method.

High quality images using unique iterative super-resolution (ISR) reconstruction, enabling 40% dose reduction*2 with 3D.

[FBP method] The path of X-ray that penetrates through a subject and reaches the detector is spatially tracked back toward the X-ray source for each pixel in the detector, positioning each projected image based on the slice height and adding pixel values of projected images to generate a sliced image of the subject.

[Problems] Since the projection angle of tomosynthesis is limited, complete regeneration of a sliced image is impossible in principle, and structures out of the focal plane appear on the sliced image as an artifact. This artifact could reduce the contrast between mammary glands and tumor masses. Therefore, additional effort in interpretation becomes necessary, such as estimating density information while referring to conventional mammography images.1)

Tomosynthesis reconstruction by conventional (FBP) method and its problems

Using filters tailored to the human body structures such as points and lines, structural patterns can be enhanced in sliced images. Even in areas with complex patterns such as calcifica-tion and mammary gland, granularity can be improved with-out deteriorating image quality.

(2) Noise reduction

With artificial intelligence technology, patterns that are not part of the human body structure are excluded as noise, estimating the three-dimensional structure of the subject with high precision.In ISR, the components of “noise without structure” are selected during reconstruction, and by excluding these noises, granularity is improved. The sharpness in images of calcification can be maintained even with low-dose exposure. As shown in Fig. 3, using filters tailored to the human body structures such as points and lines, structural patterns in sliced images are enhanced. Even in areas with complex pattern such as calcification and mammary gland, granularity can be improved without deteriorating image quality. Fig. 4 shows the effects of ISR. It is clear to see that granularity is improved while the sharp-ness of calcification is maintained.

Signal detection performance

Signal detection performance was evaluated using a CDMAM phan-tom. The CDMAM phantom has, together with grids, cylindrical metals of different diameters and thickness in each grid, and by answering the position of cylinders in each grid through visual evalu-ation, limit of visibility can be quantified (specialized software is required for the analysis. In this case, CDMAM type 3.4 and CDCOM version 1.6 were used.6)). The CDMAM phantom was placed between two 20-mm thick acrylic plates, and was exposured 16 times each with high-dose (W/Al 33 kV, 40 mAs) and low-dose (W/Al 33 kV, 25 mAs). From generated sliced images, we selected the most focused slice images and evaluated them.

Measurement results for out of plane blurring artifact

Out of plane blurring artifact was quantified using a phantom made with an acrylic sphere. A 15-mm acrylic sphere was placed on a 60-mm acrylic plate, and sliced images were reconstructed (Fig. 8). The area where the acrylic sphere existed was cut out by 30 mm × 30 mm, and the square of the difference from the background den-sity in each pixel was calculated and averaged (mean square error), in order to calculate the amount artifacts on each sliced image for both FBP and ISR. Fig. 9 shows the calculation results of the artifacts of the acrylic sphere structure. The graph was normalized by making the mean square error on the focal plane as one. Both FBP and ISR showed less artifacts as it moved away from the focal plane, but ISR clearly produced images with less oartifacts.

The evaluations of signal detection performance using ISR and FBP methods are shown in Fig. 6 (when the plotted point is located closer to the lower left corner, a smaller and lower-contrast signal can be depicted). When exposed with the equivalent dose (left), ISR improved detection performance for all diameters of cylindrical metals. When converting the improvement in detection performance of ISR to dose, ISR allowed 40% dose reduction compared to FBP (right).

Z-resolution (resolution in the depth direction) 7)

Quality control (QC) confirms equipment performance to assure the results of screening. QC of tomosynthesis has been discussed by the American College of Radiology (ACR), European Reference Organi-sation for Quality Assured Breast Screening (EUREF), International Electrotechnical Commission (IEC) and so on, as of July 2016.To evaluate artifacts that accompany reconstruction by tomosynthe-sis, in this study, we measured Z-resolution, which is the most important resolution of sliced images in the Protocol for the Quality Control of the Physical and Technical Aspects of Digital Breast Tomosynthesis Systems Draft version 0.15 8) in the EUREF guideline. Z-resolution can be calculated by full width at half maximum of pixel value of the aluminum sphere.As shown in Table 1, ISR has higher depth resolution compared to FBP.

In Fig. 6, the evaluation of signal detection performance showed that the exposure dose was comparable between FBP and ISR (left), while the exposure dose used in ISR was 40% lower than that used in FBP (right).Fig. 7 shows images of focal plane. No decrease in the visibility of cylindrical metals contained in the grid was observed with ISR despite 40% dose reduction when compared to that obtained with FBP.

(1) Artifact suppression

In the FBP method with restricted projection angles, out of plane blur-ring artifact on the slice image will occur. Using the reconstruction process ing technology based on the pr inciple of i terat ive reconstruction4), 5), we reduced out of plane blurring and successfully suppressed the occurrence of artifacts.Fig. 2 shows the comparison between an out of plane blurring artifact in a phantom image that simulates calcification (high-contrast struc-ture) and a mammary gland (low-contrast structure). With the focal position as the reference (0 mm), sliced images at the height origi-nally without structure are shown. The structure that should be in focus at the focal position (0 mm) appears as an out of plane blurring artifact with the FBP method; however, with the iterative reconstruc-tion (ISR) method, the artifact was clearly suppressed.

1) Koibuchi, Yukio; Odawara, Hiroki. Breast Tomosynthesis, Three-Dimensional X-Ray Breast Imaging Systems:Current Clinical Relevance. MEDIX. vol.56, p.23-27.2) TSAI, R. Y.; Huang, T. S. Multiframe image restoration and registration. Advances in Computer Vision and Image Processing. 1984, vol.1, p.317-339.3) Kanemura, A.; Maeda, S.; Fukuda, W.; Ishii, S.; Bayesian image superresolution and hidden variable modeling. Journal of Systems Science and Complexity. 2010, 23(1), p.116-136.

4) Nuyts, J.; Man, B. D.; Dupont, P.; Defrise, M.; Suetens, P.; Mortelmans, L. Iterative reconstruction for helical CT:a simulation study. Physics in Medicine and Biology.1998, 43(4), p.729-737.5) Fukuda, W.; Maeda, S.; Kanemura, A.; Ishii, S.; Bayesian X-ray computed tomography using material class knowledge”.2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010). Dallas, Texas. 2010-0314/19, p.2126-2129.6) Karssemeijer, N.; Thijssen, M. A. O. “Determination of

contrast-detail curves of mammography systems by automated image analysis”. Digital mammography '96:proceedings of the 3rd international workshop on digital mammography. Chicago. Elsevier, 1996, P.155-160. Note: CDCOM software and sample images are posted at www.euref.org.7) Kuwabara T and Yoshikawa K. “Physical Performance Testing of Digital Breast Tomosynthesis.” Proc. SPIE, 94123C, 1-9 (2015)8) EUREF downloads, http://www.euref.org/downloads

Iterative Reconstruction

Super-resolution is a high-resolution technology in which multiple observed images with slightly different information allow for the acquisition of images with finer spatial sampling interval.2, 3)

Some images captured from slightly different directions are aligned with finer accuracy than the spatial sampling interval of observed images, and are plotted on the same space. On this space, if pixel grids are determined at finer intervals than the pixel pitch of the detector, information will be con-tained in the grids; and thus, information that cannot be acquired by simple interpolation can be restored. Fig. 1 shows the difference in an example of phantom images that simulate calcification. The method that uses super-resolution (b) significantly improved the visibility and depiction of the shape of calcification.

Super-resolution technology

Beyond the physical limitations of the exposure equipment, ISR can generate higher-resolution images compared to the originally observed images and bring out images with high sharpness through restoration of fine structures.

Super-resolution requires high-precision alignment, in which displace-ment in projection processing is accurately considered for each pixel.

Fig. 9: Calculation results of artifacts of the acrylic sphere structure

Fig. 8: Geometric arrangement of the phantom with an acrylic sphere

Table 1 Results of Z-resolution

Each pixel in a projected image has different information

Each pixel in a projected image is slightly displaced

Fig. 6: Evaluation for signal detection performance

Fig. 5: Geometric arrangement of CDMAM phantom

ISR Iterative Super-Resolution reconstruction

Generation of low-dose and high quality tomosynthesis images by iterative reconstruction and super-resolution techniques

+ With recognition technology utilized for artificial intelligence, ISR can estimate the three-dimensional structure of a subject by repeatedly comparing projected images with sliced images and excluding the patterns that are not part of human body structure.

Iterative reconstruction

(1) Artifact suppression (2) Noise reduction

Transition to mammography that can provide high quality images with low-doseExcellent-m, image processing using artificial intelligence (AI) technology*1

PC

M C Y BL

4C 色数297mm×615mm

サイズ

受注番号

21 -3374265

得意先名

富士フイルムビジネス

エキスパート㈱様

品　　　名

マンモ画像処理

カタログ(

英語)

12/21大類

00/00■■■

00/00■■■

00/00■■■

日付・作業担当者

１

２

４

３

作業ＭＡＣ

280進行担当

■■■

裏面

M

C

Y

BL