基础信息保持和细节强化的胸部CT图像增强  

Human chest CT image enhancement based on basic information preservation and detail enhancement

作　　者：张余 张顺利 白相志[1] 张利[3] Zhang Yu;Zhang Shunli;Bai Xiangzhi;Zhang Li(School of Astronautics,Beihang University,Beijing 100191,China;School of Software Engineering,Beijing Jiaotong University,Beijing 100044,China;Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)

机构地区：[1]北京航空航天大学宇航学院,北京100191 [2]北京交通大学软件学院,北京100044 [3]清华大学电子工程系,北京100084

出　　处：《中国图象图形学报》2022年第3期774-783,共10页Journal of Image and Graphics

基　　金：国家重点研发计划资助(2019YFB1311301);国家自然科学基金项目(62171017,61871248,61976017);北京市自然科学基金项目(4202056);中国博士后科学基金项目(2021M690297)。

摘　　要：目的清晰的胸部计算机断层扫描(computed tomography,CT)图像有助于医生准确诊断肺部相关疾病,但受成像设备、条件等因素的限制,扫描得到的CT图像质量有时会不尽如人意。因此,本文提出一种简单有效的基于基础信息保持和细节强化的胸部CT图像增强算法。方法利用多尺度引导滤波器将胸部CT图像分解为一个基础信息层和多个不同尺度的细节层。基于熵的权重将胸部CT图像的多个细节层进行融合,并乘以强化系数进一步增强纹理细节。将强化的细节层和原始的基础信息层重新组合即可生成细节强化的胸部CT图像。通过此种增强方式,本文算法既能显著增强胸部CT图像的纹理细节,又能将大部分原始的基础结构信息保留到增强图像中。结果为了验证算法的有效性,将本文算法与5种优秀的图像增强算法在由3209幅胸部CT图像组成的数据集上进行测试评估。定性和定量实验结果表明,本文算法得到的增强图像保持了更多原始胸部CT图像中的基础结构信息,并更显著地强化了其中的纹理细节信息。在定量结果中,本文算法的标准差、结构相似性和峰值信噪比指标值均优于对比的5种方法,相比于性能第2的方法分别提高了4.95、0.16和4.47,即分别提升了5.61%、17.00%和16.17%。此外,本文算法增强一幅CT图像仅消耗0.10 s,有潜力应用于实际的临床诊断中。结论本文算法可以在保留大量原始结构信息的同时有效强化CT图像的细节信息,有助于医生对患者肺部疾病的精确诊断。本文算法具有较好的泛化能力,可以用于增强其他部位的CT图像和其他模态图像并取得优秀的增强结果。Objective Human chest computed tomography(CT)image analysis is a key measure for diagnosing human lung diseases.However,the current scanned chest CT images might not meet the requirement of diagnosing lung diseases accurately.Medical image enhancement is an effective technique to improve the image quality and has been used in many clinical applications,such as knee joint disease detection,breast lesion segmentation and corona virus disease 2019(COVID-19)detection.Developing new enhancement algorithms is essential to improve the quality of chest CT images.A simple yet effective chest CT image enhancement algorithm is presented based on basic information preservation and detail enhancement.Method A good chest CT image enhancement algorithm should well improve the clarity of edges or speckles in the image,while preserving much original structural information.Our human chest CT image enhancement algorithm is developed as follows.First,this algorithm exploits the advanced guided filter to decompose the CT image into multiple layers,including a base layer and multiple different scales of detail layers.Next,an entropy-based weight strategy is adopted to fuse the detail layers,which could well strengthen the informative details and suppress the texture-less layers.Afterwards,the fused detail layer is further strengthened based on an enhancement coefficient.In the end,the enhanced detail layer and the original base layer are integrated to generate the targeted chest CT image.The proposed algorithm could well enhance the details of the chest CT image,as well as transfer much original basic structural information to the enhanced image.Moreover,with the help of our algorithm,the surgeons can inspect more clear medical images without impacting their perception of the pathology information.In order to verify the effectiveness of our proposed algorithm,we have constructed a chest CT image dataset,which is composed of 20 sets/3209 chest CT images,and then evaluated our algorithm and five state-of-the-art image enhancement algori

关 键 词：肺部疾病诊断 胸部CT图像增强 图像分解 基础信息保持 细节强化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]