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Morphological and Characteristic Analysis of Upper Aero-Digestive Tract Tumour: Revealing Uncovered Facts in Digital Pathology*

机译:上部航空消化道肿瘤的形态学与特征分析:揭示数字病理学中未发现的事实*

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Upper Aero Digestive Tract cancer is treated as the primary cancer type compared to other different cancers. Exploring the morphological behaviour and characteristics of biopsy tissue sample is very significant in tumour grade analysis for proper diagnosis. After all, the manual microscopic tissue analysis process is considered as the golden standard. Traditional pathological study is still challenging and tough to overcome the manual tissue analytical barriers. To develop an efficient automated computer aided system for1. cancer tissue analysis, 2. tumour grade classification and3. survival prediction of cancer patients. The combination of different image vision techniques and microscopic image analysis tools are used to develop the state-of-the-art frameworks which will be efficient to extract different morphological features from different UADT tumours. The extracted biopsy tissue morphological features will be taken for automatic tumour grade classification that helps in assisting the pathologists to overcome the manual microscopic cancer grade classification problems. The state-of-the-art automated tissue analysis framework is developed to extract the features from the tissue samples within the short period of time. The proposed framework will be efficient for automated tissue characteristic analysis from UADT biopsy tissue samples and that can assist the pathologists to solve the inter observer variability problems.
机译:与其他不同的癌症相比,上部航空消化道癌症被视为原发性癌症类型。探索活检组织样品的形态学行为和特征在肿瘤级分析中非常显着,以进行适当的诊断。毕竟,手动微观组织分析过程被认为是黄金标准。传统的病理学研究仍然挑战,克服手动组织分析障碍仍然挑战。开发一个高效的自动化计算机辅助系统1。癌症组织分析,2.肿瘤级分类和3。癌症患者的存活预测。不同图像视觉技术和微观图像分析工具的组合用于开发最先进的框架,其将有效地提取来自不同的UADT肿瘤的不同形态学特征。提取的活检组织形态特征将采用自动肿瘤级分类,有助于协助病理学家克服人工微观癌症等级分类问题。开发了最先进的自动组织分析框架以在短时间内从组织样品中提取特征。所提出的框架将有效地从UADT活组织检查组织样品自动组织特征分析,并且可以帮助病理学家解决跨观察者的可变性问题。

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