Quest for the best endoscopic imaging modality for computer-assisted colonic polyp staging

Abstract

Background: It was shown in previous studies that high definition endoscopy, high magnification endoscopy and image enhancement technologies, such as chromoendoscopy and digital chromoendoscopy [narrow-band imaging (NBI), i-Scan] facilitate the detection and classification of colonic polyps during endoscopic sessions. However, there are no comprehensive studies so far that analyze which endoscopic imaging modalities facilitate the automated classification of colonic polyps. In this work, we investigate the impact of endoscopic imaging modalities on the results of computer-assisted diagnosis systems for colonic polyp staging.

Aim: To assess which endoscopic imaging modalities are best suited for the computer-assisted staging of colonic polyps.

Methods: In our experiments, we apply twelve state-of-the-art feature extraction methods for the classification of colonic polyps to five endoscopic image databases of colonic lesions. For this purpose, we employ a specifically designed experimental setup to avoid biases in the outcomes caused by differing numbers of images per image database. The image databases were obtained using different imaging modalities. Two databases were obtained by high-definition endoscopy in combination with i-Scan technology (one with chromoendoscopy and one without chromoendoscopy). Three databases were obtained by high-magnification endoscopy (two databases using narrow band imaging and one using chromoendoscopy). The lesions are categorized into non-neoplastic and neoplastic according to the histological diagnosis.

Results: Generally, it is feature-dependent which imaging modalities achieve high results and which do not. For the high-definition image databases, we achieved overall classification rates of up to 79.2% with chromoendoscopy and 88.9% without chromoendoscopy. In the case of the database obtained by high-magnification chromoendoscopy, the classification rates were up to 81.4%. For the combination of high-magnification endoscopy with NBI, results of up to 97.4% for one database and up to 84% for the other were achieved. Non-neoplastic lesions were classified more accurately in general than non-neoplastic lesions. It was shown that the image recording conditions highly affect the performance of automated diagnosis systems and partly contribute to a stronger effect on the staging results than the used imaging modality.

Conclusion: Chromoendoscopy has a negative impact on the results of the methods. NBI is better suited than chromoendoscopy. High-definition and high-magnification endoscopy are equally suited.

Keywords: Automated diagnosis system; Chromoendoscopy; Colonic polyps; Endoscopy; Image enhancement technologies; Imaging modalities; Narrow-band imaging.

Figure 1

Images of a polyp using digital (i-Scan) and/or conventional chromoendoscopy. WL: White light endoscopy; CC: Conventional chromoendoscopy.

Figure 2

Example images of the two classes from the employed image databases. HD: High-definition endoscopy; CCHM: High-magnification chromoendoscopy; NBI-A: High-magnification narrow-band imaging, Aachen; NBI-H: High-magnification narrow-band imaging, Hiroshima.

Figure 3

Mean classification accuracies and standard deviations of the methods per data set. HDC: High-definition chromoendoscopy; HDNC: High-definition, no chromoendoscopy; CCHM: High-magnification chromoendoscopy; NBI-A: High-magnification narrow-band imaging, Aachen; NBI-H: High-magnification narrow-band imaging, Hiroshima; A-CNN: Adapted CNN; NA-CNN: Non-adapted CNN; DT-CWT: Dual-tree complex wavelet transform; GWT: Gabor wavelet transform.

Figure 4

Box plot showing the median, the quantiles and the minimum and maximum accuracies obtained by the different feature extraction techniques per imaging modality. NBI-H: High-magnification narrow-band imaging, Hiroshima; NBI-A: High-magnification narrow-band imaging, Aachen; CCHM: High-magnification chromoendoscopy; HDC: High-definition chromoendoscopy; HDNC: High-definition, no chromoendoscopy.

Figure 5

Bar plot showing the means and standard deviations of four statistical performance measures (sensitivity, specificity, positive predictive value and negative predictive value) over the different feature extraction techniques per data set. NPV: Negative predictive value; PPV: Positive predictive value; NBI-H: High-magnification narrow-band imaging, Hiroshima; NBI-A: High-magnification narrow-band imaging, Aachen; CCHM: High-magnification chromoendoscopy; HDC: High-definition chromoendoscopy; HDNC: High-definition, no chromoendoscopy.

Figure 6

Example images of the high magnification narrow-band imaging Aachen database showing poor illumination (A) poor visibility of mucosal structures (B) and reflections (C).

Figure 7

Histograms showing the number of overexposed pixels (A) respectively the average difference of Gaussians values (B) per image of the two narrow-band imaging databases. NBI-A: High-magnification narrow-band imaging, Aachen; NBI-H: High-magnification narrow-band imaging, Hiroshima; DoG: Difference of Gaussians.