JPH03226876A - Method for varying density to picture - Google Patents
Method for varying density to pictureInfo
- Publication number
- JPH03226876A JPH03226876A JP2020475A JP2047590A JPH03226876A JP H03226876 A JPH03226876 A JP H03226876A JP 2020475 A JP2020475 A JP 2020475A JP 2047590 A JP2047590 A JP 2047590A JP H03226876 A JPH03226876 A JP H03226876A
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- 238000000034 method Methods 0.000 title claims description 19
- 210000000056 organ Anatomy 0.000 claims description 20
- 238000013459 approach Methods 0.000 claims description 2
- 210000001835 viscera Anatomy 0.000 abstract 4
- 230000006870 function Effects 0.000 description 16
- 238000010521 absorption reaction Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 230000002238 attenuated effect Effects 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000002834 transmittance Methods 0.000 description 1
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- Apparatus For Radiation Diagnosis (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
- Image Processing (AREA)
- Image Generation (AREA)
- Image Analysis (AREA)
Abstract
Description
【発明の詳細な説明】
〔産業上の利用分野〕
本発明は、３次元表示（３Ｄ表示）に好適な画像の濃度
付は方法、特に濃度に連続性を持たせるようにした画像
の濃度付は方法に関する。DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a method for adding density to an image suitable for three-dimensional display (3D display), and particularly a method for adding density to an image that provides continuity in density. is about the method.
任意の臓器を３Ｄ表示しようとする時、′主に２次元（
２Ｄ）画像１枚毎に臓器領域を抽出して、その後で３次
元的に積み上げる方法をとる。When trying to display any organ in 3D, 'mainly 2D (
2D) A method is used in which organ regions are extracted for each image and then stacked three-dimensionally.
また、３次元的な濃度勾配を、光線に対する不透明度と
対応づける方法（Ｖｏｌ、ｕｍｅ Ｒｅｎｄｅｒｉｎｇ
法）がある（１９８８年、５月、 ＩＥＥＥ、マーク・
レボイ著１１デイスプレィ・オブ・サーフニースズ・フ
ラム・ボリューム・データ”） （Ｄｉｓｐｌａｙ ｏ
ｆ Ｓｕｒｆａｃｅｓｆｒｏｍ Ｖｏｌｕｍｅ Ｄａｔ
ａ）６〔発明が解決しようとする課題〕
上記３次元的な積み上げ法は、マルチエコーによるスピ
ンエコー法のもとでのＭＲＩ画像に対しての、任意臓器
抽出処理で採用されている。In addition, a method for associating three-dimensional density gradient with opacity to light rays (Vol.
law) (May 1988, IEEE, Mark
11 Display of Surfney's Flam Volume Data by Leboy (Display o
f Surfaces from Volume Dat
a) 6 [Problems to be Solved by the Invention] The three-dimensional stacking method described above is employed in arbitrary organ extraction processing for MRI images based on the spin echo method using multi-echo.
然るに、臓器領域抽出は、閾値を設定しておき、この閾
値と画素濃度との大小比較で抽出するか否かの判定をす
る。判定の結果は、閾値内か否かの２値（“１″と’Ｏ
”）状態であり、その中間値は存在しない。しかし、中
間値が存在しない判定結果は、ノイズが混入しても排除
しにくく、正しい画像抽出及びその表示には適さない面
があった。However, when extracting an organ region, a threshold value is set, and whether or not to extract the organ region is determined by comparing the threshold value with the pixel density. The judgment result is a binary value (“1” and 'O
”) state, and there is no intermediate value. However, a determination result in which there is no intermediate value is difficult to eliminate even if noise is mixed in, and is not suitable for correct image extraction and display.
更に、不透明度を求める方法は、濃度が２値以外の値を
とることができるため、実際の臓器に近い状態での表示
が可能になるとの利点がある。Furthermore, the method of determining opacity allows the density to take values other than binary, which has the advantage of allowing display in a state close to the actual organ.
本発明の目的は、この不透明度を求めるやり方を積極的
に採用してなる画像の濃度付は方法を提供するものであ
る。An object of the present invention is to provide a method for adding density to an image by actively adopting this method of determining opacity.
本発明は、被検体から得られる画像から特定の臓器に属
する基準特性を求めておき、」二記画像の各画素の不透
明度を該基準特性に近い程大きく設定し、この不透明度
に従って濃度付けをさせた。In the present invention, standard characteristics belonging to a specific organ are determined from an image obtained from a subject, the opacity of each pixel of the image is set to be larger as it approaches the standard characteristics, and density is added according to this opacity. I made him do it.
本発明によれば、基準特性に近い程に不透明な画素濃度
となり、基準特性に遠い程に透明な画素濃度となる。従
って、基準特性の臓器が最も窩い濃度となり、且つ遠く
なるごとに低い濃度となるように表示でき、基準特性の
臓器を中心としてほぼ連続的な表示が可能になる。According to the present invention, the closer the pixel density is to the reference characteristic, the more opaque the pixel density becomes, and the further away from the reference characteristic, the more transparent the pixel density becomes. Therefore, it is possible to display such that the organ having the reference characteristic has the lowest density, and the density becomes lower as the distance increases, making it possible to display almost continuously around the organ having the reference characteristic.
尚、連続的な表示とは、本実施例ではメンバシップ関数
を採用している関係上、１”と１１０”との２値的な状
態以外に各種の中間的な値をとり得るとの意である。Note that continuous display means that since a membership function is used in this embodiment, various intermediate values can be taken in addition to the binary state of 1" and 110". It is.
第１図は本発明の実施例である。画像はメモリに格納さ
れているものとする。この画像は、マルチエコーによる
スピンエコー法で求めたＭＲＩ画像とする。FIG. 1 shows an embodiment of the invention. It is assumed that the image is stored in memory. This image is an MRI image obtained by a spin echo method using multi-echo.
第１図で、先ずＭＲＩ画像中の特定臓器の基準特性を求
める（ステップ１）。特定臓器とは、オペレータによっ
て決定される抽出臓器のことである。In FIG. 1, first, reference characteristics of a specific organ in an MRI image are determined (step 1). A specific organ is an extracted organ determined by the operator.
基準特性とは、マルチエコー法のもとてのエコー次数と
画素濃度との関係を云う。ＭＲＩ画像例を第２図に示す
。このＭＲＩ画像は、１次エコー画像１０．２次エコー
画像１１．３次エコー画像１２．４次エコー画像１３よ
り成り、これらは、それぞれメモリに格納されている。The reference characteristic refers to the relationship between the original echo order and pixel density in the multi-echo method. An example of an MRI image is shown in FIG. This MRI image consists of a first echo image 10, a second echo image 11, a third echo image 12, and a fourth echo image 13, which are each stored in the memory.
特定臓器中の任意の一点Ｐ１を指定し、この指定した点
におけるエコー次数と画素濃度とを基準特性とすること
が好ましい。It is preferable to designate an arbitrary point P1 in a specific organ and use the echo order and pixel density at this designated point as the reference characteristics.
但し、この基準特性は、事前に各種の実測値から経験的
に求めてメモリに格納しておいたものであ−
ってもよく、又は、現在のＭＲＩ画像中の特定臓器中の
任意の一点を指示してこの指示点のＭＲＩ画像中の画素
を充当させてもよい。However, this reference characteristic may be obtained empirically in advance from various measured values and stored in memory, or it may be determined from an arbitrary point in a specific organ in the current MRI image. may be designated and the pixel in the MRI image of this designated point may be assigned.
この基準特性例を第３図に示す。横軸にエコー次数、縦
軸に画素濃度を示す。実線Ａがエコー次数対画素濃度の
関係である基準特性である。基準特性は臓器の種類に応
じて種々の形体をとる。An example of this standard characteristic is shown in FIG. The horizontal axis shows the echo order, and the vertical axis shows the pixel density. A solid line A is a reference characteristic that is the relationship between echo order and pixel density. The reference characteristics take various forms depending on the type of organ.
次にステップ２で、ＭＲＩ画像の画素を走査する。走査
順序はラスクスキャン方式でよい。即ち、左上から右上
へ、左上から左下への順序である。Next, in step 2, the pixels of the MRI image are scanned. The scanning order may be a rask scan method. That is, the order is from top left to top right and from top left to bottom left.
ステップ３では、走査点での画素の実測特性と基準特性
との近さ（距離）を求める。実測特性とは、その走査点
での、ＭＲＩ画像中の、エコー次数対画素濃度との関係
を云う。・例えば、ある走査点での実測特性例を第３図
の点線Ｂで示す。In step 3, the proximity (distance) between the measured characteristic of the pixel at the scanning point and the reference characteristic is determined. The measured characteristic refers to the relationship between the echo order and the pixel density in the MRI image at that scanning point. - For example, an example of actually measured characteristics at a certain scanning point is shown by dotted line B in FIG.
近さ（距離）は、メンバシップ関係を利用して求める。Closeness (distance) is determined using membership relationships.
そのメンバシップ関数例を第４図に示す。An example of the membership function is shown in FIG.
メンバシップ関数は、基準特性と実測特性との次数毎の
差分の絶対値δの大きさを横軸にとり、縦軸にメンバシ
ップ関数値μをとり、絶対値δが大きい程に関数値μが
小さくなる特性をとる関数である。The membership function takes the magnitude of the absolute value δ of the difference for each order between the reference characteristic and the measured characteristic on the horizontal axis, and the membership function value μ on the vertical axis, and the larger the absolute value δ, the larger the function value μ. This is a function that has the characteristic of becoming smaller.
第３図では、メンバシップ関数μｍは１次エコー用、μ
２は２次エコー用、μ３は３次エコー用、μ４は４次エ
コー用の関数である。こうしたエコー次数で異なるメン
バシップ関数を採用したのは、エコー次数で近さ（距離
）が異なることがあるためである。In Figure 3, the membership function μm is for the first-order echo, μ
2 is a function for the second echo, μ3 is a function for the third echo, and μ4 is a function for the fourth echo. The reason why membership functions that differ depending on the echo order is adopted is that the proximity (distance) may differ depending on the echo order.
例えば、第３図の例に従うと、１次エコーでは差分の絶
対値δ１．２次エコーでは差分の絶対値δ２．３次エコ
ーでは差分の絶対値δ３．４次エコーでは差分の絶対値
δ４となる。これから第４図のメンバシップ関数を求め
ると、
１次エコーではμｍをとる故に、μｍ。For example, following the example in Figure 3, for the first echo, the absolute value of the difference is δ1. For the second echo, the absolute value of the difference is δ2. For the third echo, the absolute value of the difference is δ3. For the fourth echo, the absolute value of the difference is δ4. Become. If we calculate the membership function in Figure 4 from this, it will be μm because the first-order echo takes μm.
２次エコーではμ２をとる故に、μ２゜３次エコーでは
μ３をとる故に、μ３゜４次エコーではμ４をとる故に
、μ４゜となる。Since μ2 is taken for the second-order echo, μ3 is taken for the μ2° third-order echo, and μ4 is taken for the μ3° fourth-order echo, it becomes μ4°.
次に、近さ（距離）Ｍ（ｘ、ｙ）は、次式で定義する。Next, the proximity (distance) M(x, y) is defined by the following equation.
又は、
とする。ここで、ｘ、ｙとは走査位置であり、（１）式
は全エコー次数の総加算値、（２）式は全エコー次数の
総積算値である。（１）式又は（２）式によれば、各走
査点毎の近さ（距離）が数値で表現できたことになる。Or. Here, x and y are scanning positions, equation (1) is the total sum of all echo orders, and equation (2) is the sum of all echo orders. According to equation (1) or equation (2), the proximity (distance) of each scanning point can be expressed numerically.
（１）式又は（２）式で求めた距離Ｍ（ｘ、ｙ）は、第
４図かられかるように、特性が同−又は近似していれば
大きな値となり、特性が大きく異なっていれば小さな値
となる。As can be seen from Figure 4, the distance M(x, y) found using equation (1) or equation (2) will be a large value if the characteristics are the same or similar; If the value is small, the value will be small.
そこで、ステップ４では、この距離Ｍ（ｘｔｙ）に応じ
て不透明度を、下式で算出する。Therefore, in step 4, the opacity is calculated according to the distance M(xty) using the following formula.
α（ｘ、ｙ）＝Ｃ＋ Ｍ（ｘ、ｙ） ・・”（３）
ここで、α（ｘｔ ｙ）は反射率、ＣＩは定数であ−
る。反射率α（ｘ、ｙ）は、不透明度β（ｘ、ｙ）と同
じとみてよく、結局、不透明度β（ｘ、ｙ）は、
β（ｘ、ｙ）＝（、＋ Ｍ（ｘ、ｙ） ”・・（４
）として算出できる。α(x,y)=C+M(x,y)...”(3)
Here, α(xty) is the reflectance and CI is a constant. The reflectance α(x, y) can be considered to be the same as the opacity β(x, y), and after all, the opacity β(x, y) is β(x, y)=(, + M(x, y) ”...(4
) can be calculated as
次にこの不透明度β（ｘ、ｙ）から濃度を決定する（ス
テップ５）。不透明度が大きい場合、反射率か、吸収率
が大きい。吸収率が十分小さければ、不透明度は反射率
と等しくなる。従ってこの場合、不透明度の大きな物体
はど、観測者の目に入る光の量は大きくなる。さらしこ
、入射光と観測者との間の角度にも依存するため、観測
者の見る像の濃度は後述の（１０）式で近似できる。Next, the density is determined from this opacity β(x, y) (step 5). If the opacity is high, the reflectance or absorption is high. If the absorption is small enough, the opacity will be equal to the reflectance. Therefore, in this case, the more opaque the object, the greater the amount of light that enters the observer's eyes. Since it also depends on the angle between the incident light and the observer, the density of the image seen by the observer can be approximated by equation (10) described below.
ステップ６では、全画素走査終了か否かをチエツクし、
終了していなければステップ２〜５を繰返し、終了して
いれば濃度付けは終了する。In step 6, it is checked whether all pixel scanning has been completed,
If the concentration has not been completed, steps 2 to 5 are repeated, and if the concentration has been completed, the concentration is completed.
近さ（距１ｉ１１１）は（１）、 （２）式以外に下式
でもよい。The proximity (distance 1i111) may be determined by the following formula in addition to formulas (1) and (2).
η
Ｍ（ｘｔ ｙ）＝Σ ＩＲｔ−８ｚｌ −−−・
・・Ｃ５）８
（５）式は、メンバシップ関数を使用せずに、特性の次
数毎の差分の絶対値のη乗を、全次数にわたって総加算
した値を距離Ｍ （ｘ ＋ ｙ ）とした。値ηは、経
験的に定める値である。（５）式の距離Ｍ（ＸＩ ｙ）
では反射率α（ｘ、ｙ）は次式とする。η M(xt y)=Σ IRt-8zl ---・
...C5)8 Equation (5) does not use a membership function, but the distance M (x + y) is the sum of the η power of the absolute value of the difference for each order of the characteristic over all orders. did. The value η is a value determined empirically. Distance M(XI y) in equation (5)
Then, the reflectance α(x, y) is expressed as follows.
α（ｘｔ ｙ）＝Ｃｚ Ｃ３μ（ｘｔ ｙ）
・・・（６）Ｃ２＋ Ｃ３は定数である。この反射率ａ
（ｘ−＋ ｙ ）は不透明度としてよい。α(xt y)=Cz C3μ(xt y)
...(6) C2+C3 is a constant. This reflectance a
(x-+y) may be the opacity.
尚、光がある部位に入射した場合、反射する量と、その
部位を透過してゆく透過量と、その部位中に吸収される
吸収量とに分別できる。即ち、反射率＋吸収率＋透過率
＝１ ・・・・・・・・（７）である。Note that when light is incident on a certain part, it can be divided into the amount of light that is reflected, the amount of light that passes through that part, and the amount of light that is absorbed into that part. That is, reflectance+absorption factor+transmittance=1 (7).
一方、 不透明度は、 不透明度＝反射学士吸収率 ・・・・・・・・（８） である。on the other hand, The opacity is Opacity = Reflection Absorption ・・・・・・・・・(8) It is.
吸収率を略零とすると、
不透明度β（ｘ、、ｙ）＝反射率α（ｘ、ｙ）・・・・
・・（９）
となる。これが、実施例での前提事項であった。If the absorption rate is approximately zero, opacity β (x, y) = reflectance α (x, y)...
...(9) becomes. This was the premise in the example.
勿論、吸収率を考慮してもよい。Of course, absorption rate may also be taken into consideration.
一般的には、入射光重０と反射光へ■２との関係は、部
位（ｘｔ ｙ＋ ｚ）で反射すれば、ΔＩｚ＝Ｋ（Ｉｏ
ｙ ｏ） ’ ａ（ｘｔ ｙ）”’（ｔｏ）と
なって、観測者の目に入る。ここで、０とは、入射光と
観測者との間の角度（反射角度）であり、Ｋ（Ｉｏ、
Ｏ）は光源、及び光源と観測者の位置関係で決まる関数
であり、α（ｘ、ｙ）は２番目のスライス上（ｘ、ｙ）
での反射率である。点（ｘ ｔｙ）が臓器内にある時は
１．はその臓器内で減衰して工０より小さいＩＯＩにな
り、点（ｘ、ｙ）で反射ののち、再び減衰してＩＯ２と
なって観測者の目に入る。この変化は、（１０）式の反
射率α（ｘ ｔｙ）で律しきれず、Ｋ（工（１＋ ０
）なる定数に反映させればよい。Generally speaking, the relationship between the incident light weight 0 and the reflected light ■2 is as follows: ΔIz=K(Io
y o) 'a(xt y)'''(to) and enters the observer's eyes. Here, 0 is the angle between the incident light and the observer (reflection angle), and K (Io,
O) is a function determined by the light source and the positional relationship between the light source and the observer, and α(x, y) is the function (x, y) on the second slice.
This is the reflectance at When the point (x ty) is inside an organ, 1. is attenuated within the organ and becomes IOI, which is smaller than 0. After being reflected at the point (x, y), it is attenuated again and becomes IO2, which enters the observer's eyes. This change cannot be controlled by the reflectance α(x ty) in equation (10), and is expressed as
) can be reflected in the constant.
以上の実施例のシステム構成図を第５図に示す。A system configuration diagram of the above embodiment is shown in FIG.
この実施例は、ＣＰＵ２０、主メモリ２】、高速専用ハ
ードウェア２２、補助メモリ２３、ＣＲＴ２４、キーボ
ード２５、共通バス２６より成る。ＣＰＵ２０は、ＭＲ
Ｉ画像の作成処理を主メモリ２１を利用して行い、その
結果は補助メモリ２３に格納する。高速専用ハードウェ
ア２２は、第１図の処理を高速に行うための専用ハード
ウェアであり、その際、ＭＲＩ画像は補助メモリ２３に
あるものを直接アクセスするやり方の他に、主メモリ２
１に読出して高速処理をするやり方がある。また、主メ
モリ２１の代りに、高速バッファメモリを設けるやり方
もある。キーボード２５は、オペレータによって操作さ
れ、臓器の特定、基準特性の指示等に利用する。また、
ＣＲＴ２４はその際の作業画面となるが、最終的な濃度
付けの３Ｄ画面の表示用にも使う。This embodiment comprises a CPU 20, a main memory 2, high-speed dedicated hardware 22, an auxiliary memory 23, a CRT 24, a keyboard 25, and a common bus 26. The CPU 20 is MR
I-image creation processing is performed using the main memory 21, and the results are stored in the auxiliary memory 23. The high-speed dedicated hardware 22 is dedicated hardware for performing the processing shown in FIG.
There is a way to perform high-speed processing by reading data in 1. Another method is to provide a high-speed buffer memory instead of the main memory 21. The keyboard 25 is operated by the operator and is used to specify organs, specify reference characteristics, and the like. Also,
The CRT 24 serves as the work screen at that time, but is also used to display a 3D screen for final density addition.
以上の実施例では、ＭＲＩ画像の例を示したが、異なる
計測系による画像の例もありうる。この例を第６図に示
す。第６図は、ＭＲＩ画像、Ｘ線ＣＴ画像、ポジトロン
ＣＴ画像（ＰＥＴ画像）を、ＭＲＩ画像の１次、２次、
３次エコーに形式上対応させた例である。当然に同一被
検体、同一部位に対する画像である。In the above embodiment, an example of an MRI image is shown, but an example of an image obtained by a different measurement system is also possible. An example of this is shown in FIG. Figure 6 shows MRI images, X-ray CT images, and positron CT images (PET images).
This is an example that formally corresponds to a tertiary echo. Naturally, these are images of the same subject and the same region.
こうした異なる計測系の画像に対しても、経験的又は実
測的に基準特性を得ることができるため、第１図の処理
の適用が可能である。The process shown in FIG. 1 can be applied to images of such different measurement systems because the reference characteristics can be obtained empirically or measured.
〔発明の効果〕
本発明によれば、基準特性を求めておき、この基準特性
と実測特性との距離の大小に応じて濃度付けができるよ
うになった。[Effects of the Invention] According to the present invention, a reference characteristic is determined in advance, and concentration can be added according to the distance between the reference characteristic and the measured characteristic.
第１図は本発明の処理フローの実施例図、第２図はＭＲ
Ｉ画像例図、第３図は基準特性と実測特性とを示す図、
第４図は本実施例のメンバシップ関数例図、第５図は本
発明のシステム構成図、第６図は本発明の適用される他
の画像側図である。
２０・・・ＣＰＵ、２１・・主メモリ、２１・・高速専
用ハードウェア、
２３・・・補助メモリ。
特
許
出
願
人
株式会社日立メデイコFig. 1 is an example diagram of the processing flow of the present invention, Fig. 2 is an MR
I image example diagram, FIG. 3 is a diagram showing reference characteristics and measured characteristics,
FIG. 4 is an example of the membership function of this embodiment, FIG. 5 is a system configuration diagram of the present invention, and FIG. 6 is a side view of another image to which the present invention is applied. 20...CPU, 21...Main memory, 21...High-speed dedicated hardware, 23...Auxiliary memory. Patent applicant Hitachi Medico Co., Ltd.
Claims (1)
準特性を求めておき、上記画像の各画素の不透明度を該
基準特性に近い程大きく設定し、この不透明度に従って
濃度付けしてなる画像の濃度付け方法。 ２、上記画像は、マルチエコーを採用したスピンエコー
法によるＭＲＩ画像とし、上記基準特性は、このＭＲＩ
画像中の特定の臓器のマルチエコーでの次数と画素濃度
との関係とする請求項１の画像の濃度付け方法。[Claims] 1. A reference characteristic belonging to a specific organ is determined from an image obtained from a subject, and the opacity of each pixel of the image is set to be larger as it approaches the reference characteristic, and the opacity is set according to this opacity. A method for adding density to images created by adding density. 2. The above image is an MRI image using the spin echo method that employs multi-echo, and the above reference characteristics are based on this MRI image.
2. The method of densifying an image according to claim 1, wherein the relationship is between the multi-echo order of a specific organ in the image and the pixel density.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2020475A JP2878753B2 (en) | 1990-02-01 | 1990-02-01 | Image density setting method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2020475A JP2878753B2 (en) | 1990-02-01 | 1990-02-01 | Image density setting method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH03226876A true JPH03226876A (en) | 1991-10-07 |
| JP2878753B2 JP2878753B2 (en) | 1999-04-05 |
Family
ID=12028138
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020475A Expired - Fee Related JP2878753B2 (en) | 1990-02-01 | 1990-02-01 | Image density setting method |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP2878753B2 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011212219A (en) * | 2010-03-31 | 2011-10-27 | Fujifilm Corp | Projection image generation apparatus, method, and program |
-
1990
- 1990-02-01 JP JP2020475A patent/JP2878753B2/en not_active Expired - Fee Related
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011212219A (en) * | 2010-03-31 | 2011-10-27 | Fujifilm Corp | Projection image generation apparatus, method, and program |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2878753B2 (en) | 1999-04-05 |
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