Automatic computer aided analysis algorithms and system for adrenal tumors on CT images

作者：Chai, Hanchao; Guo, Yi^*; Wang, Yuanyuan^*; Zhou, Guohui

来源：Technology and Health Care, 2017, 25(6): 1105-1118.

DOI：10.3233/THC-160597

• Adrenal tumor
• sparse representations
• automatic segmentation
• tumor classification

BACKGROUND: The adrenal tumor will disturb the secreting function of adrenocortical cells, leading to many diseases. Different kinds of adrenal tumors require different therapeutic schedules. OBJECTIVE: In the practical diagnosis, it highly relies on the doctor's experience to judge the tumor type by reading the hundreds of CT images.
METHODS: This paper proposed an automatic computer aided analysis method for adrenal tumors detection and classification. It consisted of the automatic segmentation algorithms, the feature extraction and the classification algorithms. These algorithms were then integrated into a system and conducted on the graphic interface by using MATLAB Graphic user interface (GUI).
RESULTS: The accuracy of the automatic computer aided segmentation and classification reached 90% on 436 CT images.
CONCLUSION: The experiments proved the stability and reliability of this automatic computer aided analytic system.

• 出版日期2017
• 单位复旦大学