Automatic preoperative 3d model registration in laparoscopic liver resection.

PURPOSE: : Augmented Reality (AR) in Laparoscopic Liver Resection requires anatomical landmarks and the silhouette to be found on the laparoscopic image. They are used to register the preoperative 3D model obtained from CT segmentation. The existing AR systems rely on the surgeon to 1) annotate the landmarks and silhouette and 2) provide an initial registration. These non-trivial tasks require surgeon attention which may perturb the procedure. We propose methods to solve both tasks, hence registration, automatically. METHODS: : The landmarks are the lower ridge and the falciform ligament. We solve 1) by training a U-Net from a new dataset of 1415 labelled images extracted from 68 procedures. We solve 2) by a novel automatic coarse-to-fine pose estimation method, including visibility-reasoning within an iterative robust process. In addition, we propose to divide the ridge into six anatomical sub-parts, making its annotation and use in registration more accurate. RESULTS: : Our method detects the silhouette with an error equivalent to an experienced surgeon. It detects the ridge and ligament with higher errors owing to under-detection. Nonetheless, our method successfully initialises the registration with tumour target registration errors of 22.4, 14.8 and 7.2 mm for 3 clinical procedures. In comparison, the errors from manual initialisation are 30.5, 15.1 and 16.3 mm. CONCLUSION: : Our results are promising, suggesting that we have found an appropriate methodological approach.

How big is this neoplasia? live colonoscopic size measurement using the Infocus-Breakpoint.

Colonoscopy is the reference medical examination for early diagnosis and treatment of colonic diseases. This minimally invasive technique allows endoscopists to explore the colon cavity and remove neoplasias - abnormal growths of tissue - which may develop into malignant tumors. The size, shape and appearance of a neoplasia are essential cues for diagnostic. However, the size is difficult to estimate because the absolute scale of the observed tissue is not directly conveyed in the 2D colonoscopic images. An erroneous size estimate may lead to inappropriate treatment. There currently exist no solutions to reproducible neoplasia size measurement adapted to colonoscopy. We propose a colonoscopic size measurement system for neoplasias. By using a simple planar geometry, the key technical problem is reduced to resolving scale. Our core contribution is introducing the Infocus-Breakpoint (IB) that allows us to resolve scale from a regular colonoscopic video. We define the IB as the lower limit of the colonoscope's depth of field. The IB corresponds to a precise colonoscope to tissue distance, called the reference depth, which we calibrate preoperatively. We detect the IB intraoperatively thanks to two novel modules: deformable Blur-Estimating Tracking (BET) and Blur-Model Fitting (BMF). With our system, the endoscopist may interactively measure the length and area of a neoplasia in a 2D colonoscopic image directly. Our system needs no hardware modification to standard monocular colonoscopes, yet reaching a size measurement accuracy of the order of a millimeter, as shown on several phantom and patient datasets.

Monitoring of polyethylene wear in nonmetal-backed acetubular cups by digitized anteroposterior pelvic radiography.

The aim of this study was to assess polyethylene wear in a total hip prosthesis by digitized radiography of the whole pelvis in the anteroposterior (AP) plane. The three-dimensional (3-D) pose of the nonmetal-backed acetubular cup, materialized by its metal ring and the femoral head made of metal or ceramic, was estimated using iterative algebraic algorithms with inner bias correction and bootstrapping for variance reduction. Points of interest were obtained by maximizing the correlation between sampled density profiles and 3-D geometric models degraded by the modulation transfer function (MTF) of the radiographic system and the film scanner. The error in the maximal correlation estimate were inferred from noise power spectra (NPS) and allowed the calculation of the point covariance matrix. Both NPS and MTF were modeled for each stage and estimated using least-square fitting of the overall NPS model to the autospectral density function calculated in stationary regions. Comparison of the radiographic time series was made possible by the high accuracy level and 3-D matching from the cup orientation. The feasibility of the full 3-D measurement, the assumption of negligible lateral wear and its influence on AP wear are discussed on simulated and real radiographic data.