Rectal Cancer Tumor Image Segmentation Based on CNN Image Feature Recognition
DOI:
https://doi.org/10.54097/vjqr1g56Keywords:
Colorectal Cancer Tumor; Convolutional Neural Network; Image Feature Recognition.Abstract
Aiming at the problems of complex gray scale distribution, different local contrast, artifacts, and noise in CT images, this study proposes a new tumor segmentation method for rectal cancer, which employs a CNN model with a specific sequential input strategy to preprocess the images, and by comparing it with a random sequential input strategy, we demonstrate that the proposed method achieves a correctness rate of 70% in complex tumor slices. In addition to having a direct impact on the field of medical imaging, this research provides valuable insights and lessons learned for the wide application of deep learning in medical image processing.
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