Measuring the size of neoplasia in colonoscopy using Depth-From-Defocus

Colonoscopy is the reference medical examination for the diagnosis and treatment of neoplasia in gastroenterology. During the examination, the expert explores the colon cavity with a gastroscope in order to detect neoplasias - abnormal growths of tissue - and to diagnose which ones could be malignant. The Paris classification of superficial neoplastic lesions is the gold standard set of criteria for this type of diagnosis. One of the major criteria is the size. However, this is tremendously difficult to accurately estimate from images. This is because the absolute scale of the observed tissues is not directly conveyed in the 2D endoscopic image. We propose an image-based method to estimate the size of neoplasias. The core idea is to combine Depth-From-Focus (DFF) and Depth-From-Defocus (DFD). This allows us to recover the absolute scale by automatically detecting the blur/unblur breakpoint while the expert pulls the gastroscope away from a neoplasia. Our method is passive: it uses the image data only and thus does not require hardware modification of the gastroscope. We report promising experimental results on phantom and patient datasets.