An oncological patient may go through several tomographic acquisitions during a period of time, needing an appropriate registration. We propose an automatic volumetric intrapatient registration method for tumor follow‐up in pulmonary CT exams. The performance of our method is evaluated and compared with other registration methods based on optimization techniques. We also compared the metrics behavior to inspect which metric is more sensitive to changes due to the presence of lung tumors.PACS numbers: 87.57.nj; 87.57.Q‐; 87.57.N‐

Now-a-days CT scanners provide detailed morphological information of pulmonary structures, with great importance to the diagnostic and follow-up of oncological diseases. When a patient with lung cancer is submitted to several CT exams during a period of time; these exams need an appropriate registration to quantify or visualize the tumour's evolution. We propose a new method for 3D intra-patient registration of thoracic CT exams and compare its results with several 3D registration methods. The performance of these registration methods is analysed, computing several normalized figures of merit; we also explore these metrics to check which is more sensible to changes in CT exams due to the presence of lung tumours. The results with several cases of intra-patient, intra-modality registration show that the proposed method provides an accurate registration which is needed for the quantitative tracking of lesions that may effectively assist the follow-up process of oncological patients.

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