Observer-invariant histopathology using genetics-based machine learning

@article{Llor2007ObserverinvariantHU,
  title={Observer-invariant histopathology using genetics-based machine learning},
  author={Xavier Llor{\`a} and Anusha Priya and Rohit Bhargava},
  journal={Natural Computing},
  year={2007},
  volume={8},
  pages={101-120}
}
Prostate cancer accounts for one-third of noncutaneous cancers diagnosed in US men and is a leading cause of cancer-related death. Advances in Fourier transform infrared spectroscopic imaging now provide very large data sets describing both the structural and local chemical properties of cells within prostate tissue. Uniting spectroscopic imaging data and computer-aided diagnoses (CADx), our long term goal is to provide a new approach to pathology by automating the recognition of cancer in… CONTINUE READING