Since brain tumors endanger people’s living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with those datasets with character...Since brain tumors endanger people’s living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with those datasets with characters and numbers. It is difficult, however, to apply them to datasets that include brain images and medical history (alphanumeric data), especially to guarantee the accuracy. For these datasets, this paper combines the knowledge of medical field and improves the traditional decision tree. The new classification algorithm with the direction of the medical knowledge not only adds the interaction with the doctors, but also enhances the quality of classification. The algorithm has been used on real brain CT images and a precious rule has been gained from the experiments. This paper shows that the algorithm works well for real CT data.展开更多
Three-dimensional reconstructions from tomography slices are paid great attention in medical applications nowadays. This paper introduces the design and the implement of VolGraph system: a new, inexpensive, PC-based v...Three-dimensional reconstructions from tomography slices are paid great attention in medical applications nowadays. This paper introduces the design and the implement of VolGraph system: a new, inexpensive, PC-based visualization tool for three-dimensional medical reconstructions, which fully integrates the latest popular visualization algorithms ranging from classical surface rendering algorithm to volume rendering algorithms, such as Ray Casting, Splatting, and Shear-Warp.The input of VolGraph can be medical ima- ges including CT, MRI, etc, and the output can be in common image, VRML/XML or animation formats. Practice proves that the realization of a medical volume visualization system is now feasible on desktop PCs.展开更多
文摘Since brain tumors endanger people’s living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with those datasets with characters and numbers. It is difficult, however, to apply them to datasets that include brain images and medical history (alphanumeric data), especially to guarantee the accuracy. For these datasets, this paper combines the knowledge of medical field and improves the traditional decision tree. The new classification algorithm with the direction of the medical knowledge not only adds the interaction with the doctors, but also enhances the quality of classification. The algorithm has been used on real brain CT images and a precious rule has been gained from the experiments. This paper shows that the algorithm works well for real CT data.
文摘Three-dimensional reconstructions from tomography slices are paid great attention in medical applications nowadays. This paper introduces the design and the implement of VolGraph system: a new, inexpensive, PC-based visualization tool for three-dimensional medical reconstructions, which fully integrates the latest popular visualization algorithms ranging from classical surface rendering algorithm to volume rendering algorithms, such as Ray Casting, Splatting, and Shear-Warp.The input of VolGraph can be medical ima- ges including CT, MRI, etc, and the output can be in common image, VRML/XML or animation formats. Practice proves that the realization of a medical volume visualization system is now feasible on desktop PCs.
