基于内窥镜图像的儿童腺样体场景三维重建
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作者单位:

1.南方科技大学;2.南方医科大学深圳医院儿童耳鼻喉科;3.中国科学院深圳先进技术研究院

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基金项目:

国家重点研发计划;广东省自然科学基金;国家自然科学基金;南方医科大学深圳医院重点学科建设基金科研提升项目;深圳市卫生健康委菁英人才培养计划

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Adenoid Reconstruction Based on Endoscopic Image
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Affiliation:

1.Southern University of Science and Technology;2.Shenzhen Hospital of Southern Medical University;3.Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

Funding:

National Key R&D Plan; Natural Science Foundation of Guangdong Province;National Natural Science Foundation of China;Scientific Research Promotion Project of Key Discipline Construction Fund of Shenzhen Hospital of Southern Medical University;Elite Talent Training Program of Shenzhen Municipal Health Commission

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    摘要:

    腺样体肥大是导致儿童阻塞性睡眠呼吸暂停综合征的主要因素。医生通过内窥镜影像评估腺样体肥大程度及其对气道的阻塞程度。然而,由于内窥镜影像为二维图像,医生只能臆测患者腺样体区域的三维结构。这种方法严重依赖医生的相关经验和对腺样体的观察角度。腺样体区域为人体黏膜组织,且表面具有鼻腔分泌物,因此具备强反光、特征稀少、场景光滑、图像模糊等特点。根据腺样体特点,该文提出了一种基于腺样体鼻咽腔内镜图像序列的多视图三维重建算法。算法首先采用多视图立体匹配技术获取图像对应深度图的粗糙估计,然后使用网格曲面在深度空间中对粗糙的深度信息进行拟合,从而得到平滑、精细的深度图,最终通过点云融合算法获得腺样体区域稠密、精确的三维重建。仿真与真实实验表明,该文算法基于腺样体内窥镜图像序列,可实现精确、稠密和平滑的腺样体区域三维重建,并且重建结果显著优于现有三维重建算法。

    Abstract:

    Adenoid hypertrophy (AH) is a key contributor to pediatric obstructive sleep apnea syndrome (OSAS). Physicians rely on nasopharyngeal endoscopy to identify AH and the obstruction of adenoid to the airway. However, due to the limitations of 2D endoscope images, physicians have to infer the 3D structure of the adenoid region, which heavily relies on their expertise and the angle at which the adenoids are observed. The adenoid area is composed of mucosal tissue covered by nasal secretions, which may cause strong reflectivity, sparse features, smooth scenes, and blurred images. Based on these unique characteristics of the adenoids, this paper introduces a multi-view stereo algorithm based on endoscopic image sequences of the adenoid nasopharyngeal cavity. The algorithm employs multi-view stereo to first estimate a depth map corresponding to the images. Subsequently, it utilizes mesh surfaces to fit the rough depth information in the depth space, resulting in smooth and refined depth maps. This leads to a dense and precise reconstruction of the adenoid region. Both synthetic and real experimental results demonstrate that the algorithm can achieve accurate, dense, and smooth reconstruction of the adenoid area, surpassing the existing reconstruction algorithms significantly.

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引用本文

许涛,王顺成,钟建文,等.基于内窥镜图像的儿童腺样体场景三维重建 [J].集成技术,

Citing format
xu tao, wang shun cheng, zhong jian wen, et al. Adenoid Reconstruction Based on Endoscopic Image[J]. Journal of Integration Technology.

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  • 收稿日期:2024-03-07
  • 最后修改日期:2024-03-07
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  • 在线发布日期: 2024-05-20
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