本文選題：結節(jié)　切入點：TI-RADS　出處：《西南交通大學》2017年碩士論文　論文類型：學位論文

【摘要】：在醫(yī)學領域中,結節(jié)是指未經(jīng)診斷不確定良惡性的腫塊,甲狀腺結節(jié)包含良性結節(jié)和惡性結節(jié)。其中甲狀腺癌就是惡性結節(jié),良性結節(jié)多是炎癥性結節(jié)或者囊腫。由于甲狀腺結節(jié)無明顯的病癥表現(xiàn),因此病癥極易被人忽視。目前,甲狀腺疾病的常用診斷方法是超聲檢測,但是人工進行超聲診斷仍然存在一些主觀缺陷。隨著醫(yī)學影像設備的廣泛應用和數(shù)字圖像處理技術的飛速發(fā)展,利用圖像處理進行計算機輔助診斷的研究越來越多。計算機輔助診斷的主要目的是通過計算機的識別處理把超聲圖像準確地分類,為醫(yī)生和病人提供可參考的診斷結果。本文主要研究的是基于TI-RADS表的甲狀腺結節(jié)超聲圖像的特征提取和可視化。目的是研究TI-RADS等級不同的甲狀腺結節(jié)超聲圖像,把結節(jié)的分級結果和不同等級特征的差異利用圖像表現(xiàn)出來。主要研究內(nèi)容包括三部分:甲狀腺結節(jié)超聲圖像的預處理,甲狀腺結節(jié)超聲圖像的特征提取以及甲狀腺結節(jié)超聲圖像的可視化設計。超聲圖像預處理包含圖像去噪和圖像分割。針對甲狀腺圖像中的斑點噪聲,應用了基于邊緣增強的各向異性擴散模型(EEAD),在保留超聲圖像質(zhì)量的情況下去除了超聲圖像中的斑點噪聲。針對超聲圖像的結節(jié)分割,提出了基于邊緣梯度算子和形狀約束的圖割算法(Graph Cut),主要通過最小化能量函數(shù)得到結節(jié)區(qū)域。分割算法優(yōu)化了超聲圖像分割結果形狀不準確以及邊緣毛躁的現(xiàn)象。甲狀腺結節(jié)的特征提取提出了基于TI-RADS表的超聲圖像特征量化方法。把結節(jié)的特征分成形態(tài)、邊界、回聲、縱橫比和鈣化5類。通過形態(tài)學特征提取、灰度特征提取等多種方法,獲得5類共計34個數(shù)據(jù)特征,并用相關性、T檢驗和聚類等方法對特征數(shù)據(jù)進行了效果驗證。在可視化研究階段,主要工作包括聚類分析和可視化設計。聚類算法根據(jù)特征的樣本規(guī)律將其劃分成不同等級,數(shù)據(jù)可視化把分級結果利用可視化布局展示。實驗中針對單一類別的特征聚類和多類特征聚類分別應用了基于遺傳學的蟻群算法聚類(GACO)和多視圖加權聚類(TW-Kmeans)�？梢暬瘜嶒炨槍Σ煌臄�(shù)據(jù)結構設計可視化布局,實現(xiàn)針對基本信息的可視化和結節(jié)特征的可視化設計。應用圓形分區(qū)圖和矩形樹狀圖表示基本信息之間的關系。應用雷達圖、平行坐標圖和星形散點圖表現(xiàn)結節(jié)的分級結果和不同級別的特征差異。
[Abstract]:In the field of medicine, nodule is an undiagnosed benign and malignant mass. Thyroid nodule contains benign and malignant nodule. Thyroid carcinoma is a malignant nodule. Benign nodules are mostly inflammatory nodules or cysts. Because thyroid nodule has no obvious symptom, it is easy to be ignored. At present, ultrasound is commonly used to diagnose thyroid diseases. However, there are still some subjective defects in artificial ultrasound diagnosis. With the wide application of medical imaging equipment and the rapid development of digital image processing technology, The main purpose of computer-aided diagnosis is to classify ultrasonic images accurately by computer recognition. This paper mainly studies the feature extraction and visualization of thyroid nodules based on TI-RADS table. The purpose of this paper is to study the ultrasound images of thyroid nodules with different TI-RADS grades. The difference between the classification results of the nodules and the characteristics of different grades is represented by the image. The main contents of the study include three parts: the preprocessing of the ultrasonic images of the thyroid nodules, The feature extraction of thyroid nodule ultrasound image and the visualization design of thyroid nodule ultrasonic image. Ultrasonic image preprocessing includes image denoising and image segmentation. An anisotropic diffusion model based on edge enhancement was applied to remove speckle noise in ultrasonic images without preserving the quality of ultrasound images. A graph cutting algorithm based on edge gradient operator and shape constraint is proposed, which is mainly used to minimize the energy function to obtain the nodule region. The segmentation algorithm optimizes the phenomena of inaccurate shape and hairy edge of ultrasonic image segmentation results. Feature extraction of thyroid nodule A method of ultrasonic image feature quantization based on TI-RADS table is proposed. The feature of thyroid nodule is divided into shape. The boundary, echo, aspect ratio and calcification are classified into five categories. By means of morphological feature extraction and gray feature extraction, a total of 34 data features of 5 categories are obtained. In the visualization research stage, the main work includes clustering analysis and visual design. The clustering algorithm divides the feature data into different grades according to the law of the samples. Data visualization shows the hierarchical results by visual layout. In the experiment, the genetic ant colony algorithm (ACO) and the multi-view weighted clustering (TW-Kmeansan) are applied to single class and multi-class feature clustering, respectively. Design visual layout for different data structures, The basic information is visualized and the nodule feature is visualized. The relationship between the basic information is expressed by using the circular partition map and the rectangular tree chart, and the radar image is used to show the relationship between the basic information and the basic information. Parallel coordinate map and star scatter plot show nodule classification results and characteristics of different grades.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R581;TP391.41

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