調(diào)強(qiáng)放療中計(jì)算機(jī)應(yīng)用技術(shù)研究
定 價(jià):88 元
- 作者:蘭義華
- 出版時(shí)間:2022/12/1
- ISBN:9787121476105
- 出 版 社:電子工業(yè)出版社
- 中圖法分類:R815-39
- 頁碼:212
- 紙張:
- 版次:01
- 開本:16開
本書從調(diào)強(qiáng)放療的步驟入手,概括介紹常用的放療設(shè)備、照射方式、放療目的、放療的生物學(xué)原理等;重點(diǎn)介紹調(diào)強(qiáng)放療中的計(jì)算機(jī)應(yīng)用技術(shù),涉及劑量計(jì)算模型、放療計(jì)劃系統(tǒng)中的可行性問題,以及線性和非線性規(guī)劃模型、放射生物學(xué)模型、帶有劑量體積約束的規(guī)劃模型、多目標(biāo)規(guī)劃模型、照射角度選擇優(yōu)化模型等。此外,本書對通量圖的生成和調(diào)制、基于機(jī)器跳數(shù)的平滑方法和雙向葉片運(yùn)動通量圖平滑模型等進(jìn)行研究;討論自動勾畫的意義、需求和定義等,介紹閾值分割算法、區(qū)域分割算法、分水嶺分割算法和馬爾可夫隨機(jī)場分割算法等常見的圖像分割算法,重點(diǎn)介紹一種加入?yún)^(qū)域信息的測地線活動輪廓模型、一種改進(jìn)的V-Net 模型和一種基于等效生物劑量和硬件約束的一體化逆向計(jì)劃模型,并介紹凸優(yōu)化求解和劑量驗(yàn)證等。本書介紹的內(nèi)容涉及面廣,有助于讀者了解調(diào)強(qiáng)放療中的計(jì)算機(jī)應(yīng)用技術(shù),適合作為高等學(xué)校醫(yī)學(xué)影像處理相關(guān)專業(yè)研究生和高年級本科生的教材,也適合相關(guān)科研人員和對調(diào)強(qiáng)放療技術(shù)感興趣的讀者閱讀。
蘭義華,南陽師范學(xué)院計(jì)算機(jī)與信息技術(shù)學(xué)院副教授,博士,博士后。2011年12月博士畢業(yè)于華中科技大學(xué)計(jì)算機(jī)應(yīng)用技術(shù)專業(yè),2017年11月從華中科技大學(xué)軟件工程博士后流動站出站。河南省重點(diǎn)學(xué)科計(jì)算機(jī)應(yīng)用學(xué)科帶頭人,河南省教育廳學(xué)術(shù)技術(shù)帶頭人,南陽市學(xué)術(shù)技術(shù)帶頭人,南陽師范學(xué)院"臥龍學(xué)者”特聘研究員崗位入選者,計(jì)算機(jī)學(xué)會高級會員。
第1 章 引言······················································································1
1.1 研究背景及意義······································································1
1.1.1 癌癥的嚴(yán)重危害·····························································1
1.1.2 癌癥的治療方法·····························································3
1.1.3 放療對于癌癥治療的貢獻(xiàn)················································4
1.1.4 放療技術(shù)發(fā)展的巨大潛力················································5
1.2 放療技術(shù)的發(fā)展歷史································································8
1.2.1 初級放療時(shí)代································································8
1.2.2 常規(guī)放療時(shí)代································································9
1.2.3 精準(zhǔn)放療時(shí)代································································9
1.2.4 小結(jié)·········································································.10
1.3 計(jì)算機(jī)應(yīng)用技術(shù)對調(diào)強(qiáng)放療技術(shù)的支撐作用·······························.11
第2 章 放療中的硬件及放療計(jì)劃系統(tǒng)·················································.13
2.1 放療的分類·········································································.13
2.1.1 基本概念···································································.13
2.1.2 放療設(shè)備···································································.17
2.1.3 照射方式···································································.28
2.1.4 放療目的···································································.32
2.1.5 放療手段和技術(shù)··························································.33
2.1.6 劑量分割方式·····························································.37
2.2 放療的生物學(xué)原理································································.38
2.3 調(diào)強(qiáng)放療的步驟···································································.40
2.4 調(diào)強(qiáng)放療中的射線調(diào)制設(shè)備····················································.43
2.5 逆向計(jì)劃系統(tǒng)······································································.45
第3 章 調(diào)強(qiáng)放療中的規(guī)劃問題···························································.48
3.1 正向調(diào)強(qiáng)規(guī)劃和逆向調(diào)強(qiáng)規(guī)劃·················································.48
3.1.1 正向調(diào)強(qiáng)規(guī)劃·····························································.48
3.1.2 逆向調(diào)強(qiáng)規(guī)劃·····························································.49
3.2 調(diào)強(qiáng)放療中的數(shù)學(xué)優(yōu)化問題····················································.49
3.3 劑量計(jì)算模型和相關(guān)描述·······················································.50
3.4 放療計(jì)劃系統(tǒng)中的可行性問題·················································.51
3.5 調(diào)強(qiáng)放療中的規(guī)劃模型··························································.51
3.5.1 線性和非線性規(guī)劃模型················································.51
3.5.2 放射生物學(xué)模型··························································.53
3.5.3 劑量體積約束模型·······················································.56
3.5.4 劑量體積約束優(yōu)化問題················································.60
3.5.5 規(guī)范化距離信息排序···················································.63
3.5.6 混合整數(shù)規(guī)劃模型·······················································.68
3.5.7 多目標(biāo)規(guī)劃模型··························································.69
3.5.8 照射角度選擇優(yōu)化模型················································.72
第4 章 通量圖的平滑方法·································································.75
4.1 通量圖的生成和調(diào)制·····························································.75
4.2 通量圖的平滑······································································.78
4.3 圖像去噪原理······································································.79
4.4 基于機(jī)器跳數(shù)的平滑方法·······················································.83
4.4.1 基于圖像處理的平滑方法存在的問題······························.83
4.4.2 基于多葉準(zhǔn)直器的靜態(tài)調(diào)強(qiáng)放療的劑量調(diào)制過程···············.84
4.4.3 無葉片碰撞約束的模型················································.87
4.4.4 后驅(qū)葉片同步約束模型················································.88
4.4.5 前驅(qū)葉片同步約束模型················································.90
4.4.6 前后葉片中心時(shí)長同步模型··········································.91
4.4.7 舌槽欠劑量效應(yīng)的直接約束··········································.94
4.4.8 帶葉片碰撞約束的模型················································.95
4.5 雙向葉片運(yùn)動通量圖平滑模型·················································.96
4.5.1 雙向葉片運(yùn)動通量圖平滑模型介紹·································.96
4.5.2 實(shí)驗(yàn)及結(jié)果分析··························································.99
第5 章 自動勾畫技術(shù)·······································································103
5.1 自動勾畫的意義···································································103
5.2 手動勾畫的問題和自動勾畫的需求···········································104
5.3 放療中自動勾畫的定義··························································105
5.4 放療中需要自動勾畫的醫(yī)學(xué)影像··············································106
5.5 圖像分割算法······································································107
5.5.1 閾值分割算法·····························································107
5.5.2 區(qū)域分割算法·····························································113
5.5.3 分水嶺分割算法··························································118
5.5.4 馬爾可夫隨機(jī)場分割算法·············································121
5.5.5 基于活動輪廓模型的分割算法·······································125
5.5.6 基于深度學(xué)習(xí)的分割算法·············································127
5.6 一種加入?yún)^(qū)域信息的測地線活動輪廓模型及在乳腺鉬靶X 射線
攝片分割中的應(yīng)用································································130
5.6.1 一種加入?yún)^(qū)域信息的測地線活動輪廓模型························130
5.6.2 實(shí)驗(yàn)及結(jié)果分析··························································132
5.7 一種改進(jìn)的V-Net 模型及其在肺結(jié)節(jié)分割中的應(yīng)用···············139
5.7.1 一種改進(jìn)的V-Net 模型·················································139
5.7.2 實(shí)驗(yàn)及結(jié)果分析··························································142
第6 章 生物醫(yī)學(xué)與硬件約束······························································146
6.1 回歸本質(zhì)——臨床醫(yī)學(xué)目標(biāo)問題··············································146
6.2 逆向計(jì)劃的發(fā)展階段及目前存在的問題·····································146
6.3 臨床放療物理劑量特性··························································148
6.4 細(xì)胞殺滅存活理論································································149
6.5 分次治療及生物醫(yī)學(xué)劑量·······················································152
6.6 一種基于等效生物劑量和硬件約束的一體化逆向計(jì)劃模型············156
6.6.1 等效生物劑量及模型設(shè)計(jì)·············································156
6.6.2 基于多葉準(zhǔn)直器的硬件約束設(shè)計(jì)····································159
6.6.3 調(diào)強(qiáng)放療一體化逆向計(jì)劃模型構(gòu)建·································161
6.6.4 等效生物劑量模型驗(yàn)證和分析·······································162
第7 章 凸優(yōu)化求解··········································································166
7.1 放療中的凸優(yōu)化技術(shù)·····························································166
7.1.1 凸優(yōu)化技術(shù)在放療中的應(yīng)用··········································166
7.1.2 凸優(yōu)化技術(shù)的優(yōu)點(diǎn)·······················································166
7.1.3 凸優(yōu)化技術(shù)的局限性···················································166
7.2 凸集的概念·········································································167
7.3 凸函數(shù)和保凸運(yùn)算································································167
7.3.1 凸函數(shù)······································································167
7.3.2 保凸運(yùn)算···································································168
7.4 凸優(yōu)化問題·········································································168
7.4.1 凸優(yōu)化的概念·····························································168
7.4.2 全局最優(yōu)解和局部最優(yōu)解·············································169
7.5 典型的凸優(yōu)化模型································································171
7.5.1 線性規(guī)劃模型·····························································171
7.5.2 線性約束二次規(guī)劃模型················································172
7.5.3 幾何規(guī)劃模型·····························································173
7.6 多目標(biāo)優(yōu)化中的帕累托最優(yōu)····················································175
7.7 凸優(yōu)化中的內(nèi)點(diǎn)法································································175
第8 章 劑量驗(yàn)證·············································································177
8.1 放射線電離輻射特性差異·······················································177
8.2 質(zhì)量控制誤差分配································································177
8.3 多級質(zhì)量保證和驗(yàn)證·····························································178
8.4 劑量驗(yàn)證方法和工具·····························································180
8.5 獨(dú)立計(jì)算式劑量驗(yàn)證方法·······················································181
8.5.1 基于修正策略的劑量計(jì)算方法·······································181
8.5.2 基于模型策略的劑量計(jì)算方法·······································186
參考文獻(xiàn)·························································································189