Abstract: Medical image data is analysed to produce a biomarker. The data is filtered with a plurality of band-pass filters each having a different bandwidth. A texture parameter is then determined from the filtered data from each filter and the biomarker is determined as at a ratio of the texture parameters. When the biomarker is obtained from a CT image of a liver, it can be predictive of poor survival, disease extent and liver physiology of a patient following resection of colorectal cancer. When obtained from a mammographic image, the biomarker can be indicative of cancer invasion and receptor status within mammographic abnormalities. When obtained from a CT image of a lung nodule, the biomarker can be predictive of tumour stage (or grading) and tumour metabolism of a patient with non-small cell lung carcinoma (lung cancer).

Abstract: Medical image data is analysed to produce a biomarker. The data is filtered with a plurality of band-pass filters each having a different bandwidth. A texture parameter is then determined from the filtered data from each filter and the biomarker is determined as at a ratio of the texture parameters. When the biomarker is obtained from a CT image of a liver, it can be predictive of poor survival, disease extent and liver physiology of a patient following resection of colorectal cancer. When obtained from a mammographic image, the biomarker can be indicative of cancer invasion and receptor status within mammographic abnormalities. When obtained from a CT image of a lung nodule, the biomarker can be predictive of tumour stage (or grading) and tumour metabolism of a patient with non-small cell lung carcinoma (lung cancer).