Highly accurate model for prediction of lung nodule malignancy with CT scans

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://bioinformatics.astate.edu/NoduleX

Veritas: Combining Expert Opinions without Labeled Data

We consider a variation of the problem of combining expert opinions for the situation in which there is no ground truth to use for training. Even though we don’t have labeled data, the goal of this work is quite different from an unsupervised learning problem in which the goal is to cluster the data into different groups. Our work is motivated by the application of segmenting a lung nodule in a computed tomography (CT) scan of the human chest. The lack of a gold standard of truth is a critical problem in medical imaging. A variety of experts, both human and computer algorithms, are available that can mark which voxels are part of a nodule. The question is, how to combine these expert opinions to estimate the unknown ground truth. We present the Veritas algorithm that predicts the underlying label using the knowledge in the expert opinions even without the benefit of any labeled data for training. We evaluate Veritas using artificial data and real CT images to which a synthetic nodule has been added, providing a known ground truth. 1

MISSING DATA ESTIMATION FOR FULLY 3D SPIRAL CT IMAGE RECONSTRUCTION

Reconstruction algorithms that are not set up to handle in-complete datasets can lead to artifacts in the reconstructed images because the assumptions regarding the size of the image space and/or data space are violated. In this study, two recently developed geometry-independent methods 1 are applied to fully 3D multi-slice spiral CT image recon-struction. Using simulated and clinical datasets, we dem-onstrate the effectiveness of the missing data approaches in improving the quality of slices that have experienced truncation in either the transverse or longitudinal direction. • When the support of an object lies partially outside the field of view (FOV) of a CT scanner, artifacts may arise in the reconstructed image due to undersampling. • Most reconstruction algorithms implicitly assume the entire object is confined to the FOV, but if this is not the case, excessively large attenuation values may be recon-structed inside the boundary of the FOV. • The reconstruction algorithm is unaware that the mea-sured data has been affected by the object's attenuation outside the FOV, so the image in the FOV is recon-structed such that the projections through it match the measured data

Quantitative Computed Tomography Classification of Lung Nodules

View looking north with the Chateau Frontenac at left; Inside the walls of the upper town the rubble of the Château St Louis formed the base of Dufferin Terrace (1838-1878), a spacious promenade dominated by the Château Frontenac Hotel (1892-1895), a fantastical French Renaissance Revival design by Bruce Price. Baillairgé also designed the kiosks on the Terrace. [The promenade and boardwalk offers the city's best view of the Saint Lawrence River and Old Quebec. Full of vendors, street performers and scores of visitors in the summer, the boardwalk is also an excellent starting point for touring the rest of the city, descending from the staircase to the Lower Town, or riding the precipitous funicular railway. The spectacular Promenade des Gouverneurs leaves the Terrace to the south, runs beneath the Citadel, and emerges at the Plains of Abraham.] Source: Grove Art Online; http://www.oxfordartonline.com/ (accessed 7/10/2008