Cancer Data Pre-Processing Techniques
Jyotismita Chaki · 2023
Automatic detection of cancer using deep learning is a popular topic that is constantly evolving. Technological advancements in computer processors, digital imaging, and mass storage devices have enhanced the growth of cancer data processing. Cancer data processing is a technique for extracting useful information from the data. This procedure also addresses (i) quality enhancement of data, (ii) proper data representation, (iii) restoring the original cancer data from its corrupted form, and (iv) compressing the bulk amount of cancer data to improve image retrieval efficiency. Automation in cancer data processing can be divided into three categories. The first category includes algorithms that work directly with raw data. The second category includes the algorithm that uses the first category’s results for additional processing. The third and final category includes algorithms that attempt to extract semantic information from lower-level data. This chapter discusses various cancer data pre-processing techniques that are necessary for data enhancement by reducing reluctant falsifications or improving some data features that are important for additional cancer data processing and automation in retrieval, classification, detection, and diagnosis.