TWI834115B - Method for processing and displaying a skeleton image - Google Patents
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Abstract
Description
本案係為一種骨骼影像處理與顯示方法，尤指應用於受測人體的骨骼影像處理與顯示方法。This case is a bone image processing and display method, especially a bone image processing and display method applied to the human body under test.
對於疾病的診斷與治療，醫生已高度依賴醫學圖像，例如 X 光影像來進行分析與判斷。然而，這些醫學圖像中包含的影像數據係混合有骨骼、軟組織（例如肌肉、韌帶等）。而為了診斷不同病症時的需求，有時醫生希望可以有將注意力集中在骨骼或是軟組織上的不同選擇，所以需要有加強骨骼影像強度或是軟組織影像強度的不同影像顯示需求。例如，在不同的疾病診斷分析中，影像中去除軟組織的程度應該也應該有所不同。For the diagnosis and treatment of diseases, doctors have relied heavily on medical images, such as X-ray images, for analysis and judgment. However, the image data contained in these medical images is mixed with bones and soft tissues (such as muscles, ligaments, etc.). In order to meet the needs of diagnosing different diseases, sometimes doctors want to have different options to focus on bones or soft tissues, so there are different image display requirements to enhance the intensity of bone images or soft tissue images. For example, the extent to which soft tissue is removed from images should vary between diagnostic analyses.
但目前的相關技術手段並無法提供此類的解決方案，而如何解決上述傳統設備與技術手段所造成之困擾，係為發展本案技術手段之主要目的。本發明主要係有關於一種骨骼影像處理與顯示方法，應用於一受測人體中之至少一骨骼，其包含下列步驟：對該受測人體中之該骨骼進行拍攝而得出一平面影像；對該平面影像進行一干擾影像處理，用以產生出該平面影像中由非骨骼物體所造成的一干擾影像以及壓抑該干擾影像之一骨骼影像；以及因應一第一控制指令與一第二控制指令而對應顯示一第一合成影像與一第二合成影像，該第一合成影像係根據該第一控制指令之內容、該骨骼影像以及該干擾影像來運算產生，該第二合成影像係根據該第二控制指令之內容、該骨骼影像以及該干擾影像來運算產生，該第一合成影像中的該干擾影像與該骨骼影像的混色組合與該第二合成影像該干擾影像與該骨骼影像的混色組合不同。However, the current relevant technical means cannot provide such a solution, and how to solve the problems caused by the above-mentioned traditional equipment and technical means is the main purpose of developing the technical means in this case. The present invention mainly relates to a bone image processing and display method, which is applied to at least one bone in a human body under test. It includes the following steps: photographing the bone in the human body under test to obtain a planar image; The plane image is subjected to interference image processing to generate an interference image caused by non-skeletal objects in the plane image and a skeletal image that suppresses the interference image; and in response to a first control command and a second control command A first composite image and a second composite image are correspondingly displayed. The first composite image is calculated and generated based on the content of the first control instruction, the skeletal image, and the interference image. The second composite image is generated based on the third composite image. The content of the two control instructions, the bone image and the interference image are calculated to generate a color mixing combination of the interference image and the bone image in the first composite image and a color mixing combination of the interference image and the bone image in the second composite image. different.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中對該受測人體中之該骨骼進行拍攝所得出之該平面影像為一X光平面影像，而對該X光平面影像所進行之該干擾影像處理為一干擾影像分離處理，用以分離出該平面影像中由非骨骼物體所造成的該干擾影像以及消除該干擾影像後之該骨骼影像。According to the above concept, in the bone image processing and display method described in this case, the plane image obtained by photographing the bone in the human body is an X-ray plane image, and the X-ray plane image is The interference image processing is an interference image separation process, which is used to separate the interference image caused by non-skeletal objects in the plane image and the skeletal image after eliminating the interference image.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中該第一控制指令之內容包含一第一伽瑪校正（Gamma correction）處理，該第一合成影像係根據該第一伽瑪校正處理來對該骨骼影像進行調整後再與該干擾影像進行一第一混色疊合運算來完成，該第二控制指令之內容包含一第二伽瑪校正處理，該第二合成影像係根據該第二伽瑪校正處理來對該骨骼影像進行調整後再與該干擾影像進行一第二混色疊合運算來完成。According to the above concept, in the bone image processing and display method described in this case, the content of the first control instruction includes a first gamma correction process, and the first composite image is based on the first gamma correction process. This is accomplished by adjusting the skeletal image and then performing a first color mixing superposition operation with the interference image. The content of the second control instruction includes a second gamma correction process. The second composite image is based on the second The gamma correction process is used to adjust the bone image, and then a second color mixing superposition operation is performed with the interference image to complete.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中對應該第一混色疊合運算之一第一透明度參數與對應該第二混色疊合運算中之一第二透明度參數不同。According to the above idea, in the skeleton image processing and display method described in this case, a first transparency parameter corresponding to the first color mixing and superimposition operation is different from a second transparency parameter corresponding to the second color mixing and superposition operation.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中該第一控制指令與該第二控制指令皆由一指標移動的軌跡所定義，該第一伽瑪校正處理與該第二伽瑪校正處理係由該指標移動的一第一軌跡來定義，而該第一透明度參數與該第二透明度參數則由該指標移動的一第二軌跡來定義，該第一軌跡與該第二軌跡不平行。According to the above concept, in the skeleton image processing and display method described in this case, the first control instruction and the second control instruction are both defined by the trajectory of a pointer movement, and the first gamma correction processing and the second gamma The correction process is defined by a first trajectory of the pointer movement, and the first transparency parameter and the second transparency parameter are defined by a second trajectory of the pointer movement, and the first trajectory and the second trajectory are different. parallel.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中該第一軌跡為該指標的一水平移動軌跡，而該第二軌跡為該指標的一垂直移動軌跡。According to the above idea, in the skeleton image processing and display method described in this case, the first trajectory is a horizontal movement trajectory of the pointer, and the second trajectory is a vertical movement trajectory of the pointer.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中該第一控制指令或該第二控制指令中包含有一混色組合預設值，該混色組合預設值根據該患者的性別、年齡或體重資料來進行調整。According to the above idea, in the bone image processing and display method described in this case, the first control instruction or the second control instruction includes a preset value of a mixed color combination, and the preset value of the mixed color combination is based on the patient's gender, age or weight information to make adjustments.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中該第一控制指令或該第二控制指令中包含有一混色組合預設值，該混色組合預設值根據該平面影像中所採集到的骨骼特徵或疾病診斷內容來自動進行調整。According to the above idea, in the skeleton image processing and display method described in this case, the first control instruction or the second control instruction includes a preset value of a mixed color combination, and the preset value of the mixed color combination is based on the values collected in the plane image. skeletal characteristics or disease diagnosis content to automatically adjust.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中該第一控制指令或該第二控制指令中包含有一混色組合預設值，該混色組合預設值根據該平面影像中包含有整體亮度與分辨率的影像特徵、包含有模態型號、曝光時間的模態屬性或包含有站立或躺下的拍攝型態來自動進行調整。According to the above idea, in the skeleton image processing and display method described in this case, the first control instruction or the second control instruction includes a preset value of a mixed color combination, and the preset value of the mixed color combination is based on the overall shape contained in the plane image. Image characteristics of brightness and resolution, modal attributes including modal model, exposure time, or shooting modes including standing or lying down are automatically adjusted.
根據上述構想，本案所述之骨骼影像處理與顯示方法，其中為得出該平面影像而對該受測人體中之該骨骼所進行之拍攝，其為一單一能量的X光照射。According to the above concept, the bone image processing and display method described in this case involves photographing the bones in the human body under test in order to obtain the plane image, which is a single-energy X-ray irradiation.
為了能對本發明之上述構想有更清楚的理解，下文特舉出多個實施例，並配合對應圖式詳細說明如下。In order to have a clearer understanding of the above-mentioned concepts of the present invention, multiple embodiments are listed below and described in detail with the corresponding drawings.
為了解決上述的問題，本案係發展出一種骨骼影像處理與顯示方法，其步驟流程示意圖請參見圖1之所示，其主要可應用於一受測人體中之至少一骨骼，其主要包含下列步驟：對該受測人體中之該骨骼進行拍攝而得出一平面影像(步驟11)；對該平面影像進行一干擾影像處理，用以產生出該平面影像中由非骨骼物體(例如肌肉、韌帶等軟組織或衣物)所造成的一干擾影像以及壓抑該干擾影像之一骨骼影像(步驟12)；以及因應一第一控制指令與一第二控制指令而對應顯示一第一合成影像與一第二合成影像，而其中該第一合成影像係根據該第一控制指令之內容、該骨骼影像以及該干擾影像來運算產生，該第二合成影像係根據該第二控制指令之內容、該骨骼影像以及該干擾影像來運算產生，該第一合成影像中的該干擾影像與該骨骼影像的混色組合與該第二合成影像該干擾影像與該骨骼影像的混色組合不同(步驟13)。In order to solve the above problems, this case has developed a bone image processing and display method. The schematic flow chart of its steps is shown in Figure 1. It can be mainly applied to at least one bone in a human body under test. It mainly includes the following steps. : Photograph the bones in the human body under test to obtain a planar image (step 11); perform an interference image processing on the planar image to generate non-skeletal objects (such as muscles, ligaments, etc.) in the planar image. An interference image caused by soft tissue or clothing) and a bone image that suppresses the interference image (step 12); and correspondingly displaying a first composite image and a second control command in response to a first control command and a second control command A synthetic image, wherein the first synthetic image is generated based on the content of the first control instruction, the skeletal image and the interference image, and the second synthetic image is generated based on the content of the second control instruction, the skeletal image and The interference image is generated by calculation, and the color mixing combination of the interference image and the bone image in the first composite image is different from the color mixing combination of the interference image and the bone image in the second composite image (step 13).
而上述對該受測人體中之該骨骼進行拍攝可以是單一能量的X光照射，而所得出之該平面影像可以是常見的X光平面影像(如圖2A之所示)，而對該X光平面影像所進行之該干擾影像處理可以是一種干擾影像分離處理，其目的是用以分離出該平面影像2中由非骨骼物體所造成的該干擾影像20(如圖2B之所示)以及消除該干擾影像後之該骨骼影像21(如圖2C之所示)。本案的干擾影像分離處理可由不同階段的各種影像處理步驟所組成，用以提供最佳的影像顯示結果，例如是現存的影像處理方法(例如影像去背演算法)，用以自動將非骨骼物體所產生的影像予以剔除，並可以將非骨骼物體分離出成為一干擾影像，進而產生畫面較乾淨的骨骼影像以及該干擾影像。而且此一干擾影像去除方法也可以利用人工智慧技術來進行訓練，用以增加其準確度。The above-mentioned photographing of the bones in the human body under test can be a single-energy X-ray irradiation, and the resulting plane image can be a common X-ray plane image (as shown in Figure 2A), and for the X-ray The interference image processing performed on the light plane image may be an interference image separation process, the purpose of which is to separate the interference image 20 caused by non-skeletal objects in the plane image 2 (as shown in Figure 2B) and The bone image 21 after eliminating the interference image (as shown in Figure 2C). The interference image separation process in this case can be composed of various image processing steps at different stages to provide the best image display results. For example, existing image processing methods (such as image deconvolution algorithms) are used to automatically separate non-skeletal objects. The generated image is eliminated, and non-skeletal objects can be separated into an interference image, thereby producing a cleaner skeletal image and the interference image. Moreover, this interference image removal method can also be trained using artificial intelligence technology to increase its accuracy.
而上述控制方法需要實時反應生效，使用者才能立刻看到干擾影像去除的效果，方便使用者進行診斷和下一步的透明度參數調整。舉例來說：當干擾影像去除功能被啟用時，醫生可以按住滑鼠的左鍵並上下垂直移動來調整透明度參數級別。此外，醫生可以按住滑鼠左鍵左右水平移動來調整圖像增強參數(例如伽瑪校正參數)。通過這種方式，可以實時完成透明度參數以及圖像增強參數的調整。The above control method requires real-time response to take effect, so that the user can immediately see the effect of interference image removal, which is convenient for the user to make diagnosis and adjust the transparency parameters in the next step. For example: when the interference image removal function is enabled, the doctor can hold down the left button of the mouse and move it vertically up and down to adjust the transparency parameter level. In addition, the doctor can hold down the left mouse button and move horizontally left and right to adjust image enhancement parameters (such as gamma correction parameters). In this way, the adjustment of transparency parameters and image enhancement parameters can be completed in real time.
詳言之，步驟13中之該第一控制指令之內容可以包含一第一伽瑪校正（Gamma correction）處理，而該第一合成影像係根據該第一伽瑪校正處理來對該骨骼影像進行調整後再與該干擾影像進行一第一混色疊合運算來完成，至於該第二控制指令之內容則可包含一第二伽瑪校正處理，該第二合成影像係根據該第二伽瑪校正處理來對該骨骼影像進行調整後再與該干擾影像進行一第二混色疊合運算來完成。Specifically, the content of the first control instruction in step 13 may include a first gamma correction process, and the first composite image is performed on the skeletal image according to the first gamma correction process. After adjustment, a first color mixing superposition operation is performed with the interference image to complete. As for the content of the second control instruction, a second gamma correction process can be included. The second composite image is based on the second gamma correction. The process is performed to adjust the bone image and then perform a second color mixing superposition operation with the interference image to complete.
更甚者，在上述的步驟中，對應於該第一混色疊合運算之一第一透明度參數與對應該第二混色疊合運算中之一第二透明度參數不同。而且，該第一控制指令與該第二控制指令可由一指標移動的軌跡來進行內容調整，例如，該第一伽瑪校正處理與該第二伽瑪校正處理係由該指標移動的一第一軌跡來定義，而該第一透明度參數與該第二透明度參數則由該指標移動的一第二軌跡來定義，而該第一軌跡與該第二軌跡不平行。例如圖3之所示，該第一軌跡31為該指標30的一水平移動軌跡，而該第二軌跡32為該指標30的一垂直移動軌跡。於是，透過指標30的水平移動，便可以控制伽瑪校正參數的大小，而指標30的垂直移動，便可調整透明度參數的大小。What's more, in the above steps, a first transparency parameter corresponding to the first color mixing and overlay operation is different from a second transparency parameter corresponding to the second color mixing and overlay operation. Moreover, the content of the first control instruction and the second control instruction can be adjusted based on the movement trajectory of a pointer. For example, the first gamma correction process and the second gamma correction process are based on a first movement trajectory of the pointer. The first transparency parameter and the second transparency parameter are defined by a second trajectory of the pointer movement, and the first trajectory and the second trajectory are not parallel. For example, as shown in FIG. 3 , the
請參見圖4A與圖4B，其係在不同混色疊合的條件下的合成影像示意圖，其中圖4A係為25% 干擾影像 + 100% 骨骼影像之混色疊合條件下的合成影像示意圖，圖4B則為50%干擾影像 + 100% 骨骼影像之混色疊合條件下的另一合成影像示意圖。由圖可以看出，兩者呈現不同的影像細節，可提供使用者根據不同需求來呈現。另外，本案也可以提供其它不同的控制行為，例如按住滑鼠左鍵並順時針/逆時針旋轉、按住 ctrl + 按住滑鼠左鍵並向上/向下或向左/向右移動等等。Please refer to Figure 4A and Figure 4B, which are schematic diagrams of the composite image under different mixed color superposition conditions. Figure 4A is a schematic diagram of the composite image under the mixed color superposition condition of 25% interference image + 100% bone image. Figure 4B This is another synthetic image schematic diagram under the condition of mixed color superposition of 50% interference image + 100% bone image. As can be seen from the picture, the two present different image details, which can be presented by users according to different needs. In addition, this case can also provide other different control behaviors, such as holding down the left mouse button and rotating clockwise/counterclockwise, holding down ctrl + holding down the left mouse button and moving up/down or left/right, etc. wait.
如此一來，使用者透過滑鼠或觸控面板來控制指標30的移動軌跡，便可以調整該合成影像的整體明亮度以及該骨骼影像與該干擾影像的混合比例，進而產生出加強骨骼影像強度或是軟組織影像強度的不同影像來進行顯示，以滿足使用者在不同情況下的各種需求。而且，因為患者的性別、年齡或體重資料可能會直接影響影像顯示的需求，所以上述該等控制指令中還可包含有一混色組合預設值，該混色組合預設值可以根據該患者的性別、年齡或體重資料來完成自動調整。更甚者，該混色組合預設值還可以根據該平面影像中所採集到的骨骼特徵（例如脛骨大小、股骨大小）或疾病診斷（如關節間隙狹窄、骨贅等的診斷）來自動進行調整。另外，上述之混色組合預設值還可以根據該平面影像中之影像特徵（如整體亮度、分辨率）、模態屬性（如X光機的模態型號、曝光時間）或拍攝型態（如站立或躺下）來自動進行調整。如此一來，將可以更有助於系統自動先顯示出一個效果比較好的合成影像。In this way, the user controls the movement trajectory of the
詳言之， 由於每個醫生的觀看X光影像的偏好不同，而本案便可以為醫生提供了一種骨骼影像處理與顯示方法的方法。在不同的疾病分析中，干擾影像去除程度應該也應該有所不同。因此，醫生應該有辦法調整干擾影像去除參數來改變圖像的顯示效果。而且除了干擾影像去除之外，本案還具有圖像增強功能。本案使得圖像增強參數可以調整，讓醫生可根據患者、疾病和醫學圖像輸出的不同情況來進行選擇。另外，醫學影像的拍攝程序會因患者的情況而異（有些人可能無法使用某種姿勢，即標準姿勢）。拍攝過程會根據放射技師或放射科醫師的培訓、專業和細心程度而有所不同。我們應該有辦法讓醫生根據這些變化來調整干擾影像去除參數。Specifically, since each doctor has different preferences for viewing X-ray images, this case can provide doctors with a method of processing and displaying bone images. The degree of interfering image removal should also vary in different disease analyses. Therefore, doctors should have a way to adjust the interference image removal parameters to change the display effect of the image. In addition to interference image removal, this case also has image enhancement functions. This case allows image enhancement parameters to be adjusted, allowing doctors to make choices based on different situations of patients, diseases, and medical image output. In addition, the procedures for taking medical images vary depending on the patient's condition (some people may not be able to use a certain position, i.e. the standard position). The filming process will vary based on the training, expertise and care of the radiographer or radiologist. We should have a way for physicians to adjust interfering image removal parameters based on these changes.
另外，本案系統還可以支持原始圖像與干擾去除後圖像的多個並排比較。並且可以通過醫療數位影像傳輸協定（DICOM，Digital Imaging and Communications in Medicine）之圖像工具進一步調整原始圖像。例如，醫生可以看到佈局為 2x2 的四張圖像顯示， 第一個顯示為原始(RAW )的圖像、第二個顯示為亮度/對比度增強的圖像，第三個顯示為干擾去除後的顯示圖像，第四個顯示為醫生自行調整完成的圖像。如此一來將可以讓醫生能夠靈活地深入分析。In addition, the system in this case can also support multiple side-by-side comparisons of the original image and the image after interference removal. And the original image can be further adjusted through the image tool of Digital Imaging and Communications in Medicine (DICOM). For example, the doctor can see a four-image display with a 2x2 layout. The first is the original (RAW) image, the second is the brightness/contrast enhanced image, and the third is after interference removal. display image, and the fourth display is the image completed by the doctor's own adjustment. This will give doctors the flexibility to drill down deeper.
另外，本案還可以根據系統在圖像上採集的特徵（如脛骨大小、股骨大小）以及相關的疾病診斷（如關節間隙狹窄、骨贅等的OA診斷），系統還可以自動調整去肉參數和調整的比例和圖像增強參數，用於更好的去肉渲染，可以協助醫生進行診斷。In addition, in this case, based on the characteristics collected by the system on the image (such as tibia size, femur size) and related disease diagnosis (such as OA diagnosis of joint space narrowing, osteophytes, etc.), the system can also automatically adjust the fleshing parameters and Adjusted scaling and image enhancement parameters for better flesh-free rendering that can assist doctors in diagnosis.
綜上所述，雖然本發明以實施例揭露如上，但並非用以限定本發明。本發明所屬技術領域中具有通常知識者，在不脫離本發明之技術精神和範圍內，當可作各種之更動與潤飾。因此，本發明之保護範圍當視後附之申請專利範圍請求項所界定者為準。In summary, although the present invention is disclosed in the above embodiments, they are not intended to limit the present invention. Those with ordinary knowledge in the technical field to which the present invention belongs can make various modifications and modifications without departing from the technical spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the appended patent application claims.
2:平面影像 20:干擾影像 21:骨骼影像 30:指標 31:第一軌跡 32:第二軌跡 2: Flat image 20:Interference image 21:Skeleton image 30:Indicator 31:First track 32:Second track
圖1，其係本案所發展出來的骨骼影像處理與顯示方法的較佳實施例步驟流程示意圖。
圖2A，其係本案對於該受測人體中之該骨骼進行X光拍攝所得出之X光平面影像示意圖。
圖2B，其係本案對該X光平面影像進行干擾影像處理後所分離出之干擾影像示意圖。
圖2C，其係本案對該X光平面影像進行消除該干擾影像後之該骨骼影像示意圖。
圖3，其係本案系統中關於指標30的第一軌跡與第二軌跡之示意圖。
圖4A與圖4B，其係在不同混色疊合的條件下的合成影像示意圖。
Figure 1 is a schematic flow chart of a preferred embodiment of the bone image processing and display method developed in this case.
Figure 2A is a schematic diagram of the X-ray plane image obtained by taking X-rays of the bones in the human body under test in this case.
Figure 2B is a schematic diagram of the interference image separated after interference image processing on the X-ray plane image in this case.
Figure 2C is a schematic diagram of the bone image after eliminating the interference image from the X-ray plane image in this case.
Figure 3 is a schematic diagram of the first trajectory and the second trajectory of the
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| CN1556504A (en) * | 2004-01-09 | 2004-12-22 | 上海第二医科大学附属第九人民医院 | CT medical imaging method |
| TWM458747U (en) * | 2013-03-27 | 2013-08-01 | Regulus Technologies Co Ltd | Image processing module |
| TWI709147B (en) * | 2019-10-16 | 2020-11-01 | 中國醫藥大學附設醫院 | System of deep learning neural network in prostate cancer bone metastasis identification based on whole body bone scan images |
| TW202116253A (en) * | 2019-07-04 | 2021-05-01 | 新加坡商派拉梅維爾私人有限公司 | Diagnosis support program |
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| CN1556504A (en) * | 2004-01-09 | 2004-12-22 | 上海第二医科大学附属第九人民医院 | CT medical imaging method |
| TWM458747U (en) * | 2013-03-27 | 2013-08-01 | Regulus Technologies Co Ltd | Image processing module |
| TW202116253A (en) * | 2019-07-04 | 2021-05-01 | 新加坡商派拉梅維爾私人有限公司 | Diagnosis support program |
| TWI709147B (en) * | 2019-10-16 | 2020-11-01 | 中國醫藥大學附設醫院 | System of deep learning neural network in prostate cancer bone metastasis identification based on whole body bone scan images |
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