chexnet: CheXNet: Radiologist-Level Pneumonia Detection on Chest...

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

Description

ANTsXNet reproduction of https://arxiv.org/pdf/1711.05225.pdf. This includes our own network architecture and training (including data augmentation).

Usage

chexnet(
  image,
  lungMask = NULL,
  checkImageOrientation = FALSE,
  useANTsXNetVariant = TRUE,
  includeTuberculosisDiagnosis = FALSE,
  verbose = FALSE
)

Arguments

image	input 3-D lung image.
lungMask	ANTsImage. If None is specified, one is estimated.
checkImageOrientation	Check the correctness of image orientation, i.e., flipped left-right, up-down, or both. If TRUE, attempts to correct before prediction.
useANTsXNetVariant	Use an extension of the original chexnet approach by adding a left/right lung masking and including those two masked regions in the red and green channels, respectively.
includeTuberculosisDiagnosis	Include the output of an additional network trained on TB data but using the ANTsXNet variant chexnet data as the initial weights.
verbose	print progress.

Details

Includes a network for checking the correctness of image orientation, i.e., flipped left-right, up-down, or both.

Disease categories: Atelectasis Cardiomegaly Consolidation Edema Effusion Emphysema Fibrosis Hernia Infiltration Mass No Finding Nodule Pleural Thickening Pneumonia Pneumothorax

Value

classification scores for each of the 14 or 15 categories.

Author(s)

Tustison NJ

Examples

## Not run: 
library( ANTsRNet )

## End(Not run)

ANTsX/ANTsRNet documentation built on Nov. 21, 2024, 4:07 a.m.