Texture-Based CAD for Cancer Screening from 3D Images

描述（由申请人提供）：结直肠癌是美国第三大最常见的诊断癌症，也是癌症死亡的第二大原因。膀胱癌是美国癌症死亡的第五大原因。癌症通常在患者出现症状后的晚期才被诊断出来，这解释了其高死亡率。由于大多数结肠癌是由5至15年的息肉恶变引起的，因此提倡筛查直径小于1 cm的小息肉。不幸的是，大多数人都没有遵循这个建议。膀胱肿瘤分期也存在类似的情况。该项目的健康相关性是通过提供一种方便、几乎无风险的程序，大大增加愿意参加筛查计划的人数。虚拟结肠镜检查（VCon）和虚拟膀胱镜检查（VCys），作为一种新的程序，其中计算机断层扫描（CT）或磁共振（MR）图像的患者的腹部和计算机可视化系统是用来虚拟导航内构建的三维模型的结肠或膀胱，已经证明了结肠癌筛查和膀胱肿瘤评估的潜力。多年来，我们一直致力于VCon和VCys的开发。该项目的广泛，长期目标是开发基于3D纹理的计算机辅助检测（txCAD）技术，以促进VCon和VCys作为准确，具有成本效益，非侵入性，舒适的技术来筛选大部分人群。第一阶段的具体目标是：（1）开发减轻部分体积效应的组织混合图像分割。(2)提取粘膜层并从分割中清洁中空器官的管腔空间。(3)以高灵敏度和合理的假阴性识别粘膜层中的可疑斑块。(4)以获得每一个可疑补丁的全部体积。第二阶段的目标是：（5）从每个可疑体积中提取3D几何，形态和纹理信息。(6)使用学习机对提取的特征进行分类，以消除误报。(7)在超过200例病例的患者数据库上评价申报txCAD的性能。据推测，拟议的txCAD将显着提高检测性能相比，以前的几何为基础的CAD（sfCAD），并大大减少了医生的互动时间与我们开发的VCon和VCys系统。

DESCRIPTION (provided by applicant): Colorectal carcinoma is the third most commonly diagnosed cancer and the second leading cause of death from cancer in the United States. Bladder cancer is the fifth cause of cancer deaths in the United States. Often the cancers are diagnosed at an advanced stage after the patients have developed symptoms, explaining their high mortality rates. Since most colon cancers arise from polyps over a 5 to 15 year period of malignant transformation, screening programs to detect small polyps less than 1 cm in diameter have been advocated. Unfortunately most people do not follow this recommendation. A similar situation exists for bladder tumor staging. The health relatedness of this project is to dramatically increase the number of people willing to participate in screening programs by offering a convenient, nearly risk-free procedure. Virtual colonoscopy (VCon) and virtual cystoscopy (VCys), as new procedures in which computed tomographic (CT) or magnetic resonance (MR) images of the patient's abdomen are taken and a computer visualization system is used to virtually navigate within a constructed 3D model of the colon or bladder, has demonstrated the potential for colon cancer screening and bladder tumor evaluation. We have been contributing the VCon and VCys development for several years. The broad, long-term objective of this project is to develop 3D texture-based computer aided detection (txCAD) techniques to facilitate VCon and VCys as accurate, cost-effective, non-invasive, comfortable techniques to screen large segments of the population. The Phase I specific aims are: (1) To develop tissue-mixture image segmentation mitigating the partial volume effect. (2) To extract the mucosa layer and cleanse the lumen space of the hollow organs from the segmentation. (3) To identify suspicious patches in the mucosa layer with high sensitivity and reasonable false negatives. (4) To obtain the entire volume of each suspicious patch. The Phase II aims are: (5) To extract 3D geometrical, morphological and texture information from each suspicious volume. (6) To classify the extracted features using learning machine to eliminate false positives. (7) To evaluate the performance of the proposed txCAD on a patient database of over 200 cases. It is hypothesized that the proposed txCAD will significantly improve the detection performance compared to previous geometry-based CAD (sfCAD), and dramatically reduces the physician's interaction time with our developed VCon and VCys systems.