Computer-aided small bowel tumor detection for capsule endoscopy

Objective

Capsule endoscopy is useful in the diagnosis of small bowel diseases. However, the large number of images produced in each test is a tedious task for physicians. To relieve burden of physicians, a new computer-aided detection scheme is developed in this study, which aims to detect small bowel tumors for capsule endoscopy.

Methods and materials

A novel textural feature based on multi-scale local binary pattern is proposed to discriminate tumor images from normal images. Since tumor in small bowel exhibit great diversities in appearance, multiple classifiers are employed to improve detection accuracy. 1200 capsule endoscopy images chosen from 10 patients’ data constitute test data in our experiment.

Results

Multiple classifiers based on k-nearest neighbor, multilayer perceptron neural network and support vector machine, which are built from six different ensemble rules, are experimented in three different color spaces. The results demonstrate an encouraging detection accuracy of 90.50%, together with a sensitivity of 92.33% and a specificity of 88.67%.

Conclusion

The proposed scheme using color texture features and classifier ensemble is promising for small bowel tumor detection in capsule endoscopy images.     

Enhanced diagnostic yield with prolonged small bowel transit time during capsule endoscopy

Background: The effect of small bowel transit time (SBTT) on diagnostic yield during capsule endoscopy (CE) has not been previously evaluated. Our study aim was to assess the effect of SBTT on the likelihood of detecting intestinal pathology during CE. Methods: We reviewed collected data on CE studies performed at Johns Hopkins Hospital from January 2006 to June 2007. In patients investigated for anemia or obscure bleeding, the following lesions were considered relevant: ulcers, erosions, AVMs, red spots, varices, vascular ectasias, and presence of blood. In patients with diarrhea or abdominal pain, ulcers, erosions, and blood were considered relevant. Age, gender, study indication, hospital status, and quality of bowel preparation were identified as candidate risk factors affecting SBTT. Univariate logistic and linear regression analyses were performed to study the effect of SBTT on diagnostic yield. Results: Total of 212 CE studies were analyzed; most were in outpatients (n=175, 82.9%) and with excellent bowel preparation (n=177, 83.5%). Mean SBTT was 237.0min (3.9hrs). Age, gender, bowel prep, hospital status, and study indication did not significantly affect SBTT. However, increased SBTT was independently associated with increased diagnostic yield; OR=1.7 in SBTT=2-4hr (p=0.41), OR=1.8 in SBTT=4-6hrs (p=0.30), OR=9.6 in SBTT=6-8hrs (p=0.05). Conclusion: Prolonged SBTT during CE (>6 hr) is associated with an increased diagnostic yield. This may be due to a positive effect on image quality during a “slower” study. The use of promotility agents may adversely affect the ability of CE to detect significant intestinal pathology.     

Primary care diagnostic technology update: point-of-care testing for glycosylated haemoglobin

Clinical Question

In the monitoring of patients with type 1 and type 2 diabetes, what advantages does point-of-care HbA_1c testing provide over current practice     

Detection of contractions in adaptive transit time of the small bowel from wireless capsule endoscopy videos

Recognizing intestinal contractions from wireless capsule endoscopy (WCE) image sequences provides a non-invasive method of measurement, and suggests a solution to the problems of traditional techniques for assessing intestinal motility. Based on the characteristics of contractile patterns and information on their frequencies, the contractions can be investigated using essential image features extracted from WCE videos. In this study, we proposed a coherent three-stage procedure using temporal and spatial features. The possible contractions are recognized by changes in the edge structure of the intestinal folds in Stage 1 and evaluating similarity features in consecutive frames in Stage 2. In order to take account of the properties of contraction frequency, we consider that the possible contractions are located within windows including consecutive frames. The size of these contraction windows is adjusted according to the passage of the WCE. These procedures aim to exclude as many non-contractions as possible. True contractions are determined through spatial analysis of directional information in Stage 3. Using the proposed method, 81% of true contractions are detected with a 37% false alarm rate for evaluations in the experiments. The overall performance of this method is better than that of previous methods, in terms of both the quality and quantity indices. The results suggest feasible data for further clinical applications.     

Detection of small bowel tumor in wireless capsule endoscopy images using an adaptive neuro-fuzzy inference system

Automatic diagnosis tool helps physicians to evaluate capsule endoscopic examinations faster and more accurate. The purpose of this study was to evaluate the validity and reliability of an automatic post-processing method for identifying and classifying wireless capsule endoscopic images, and investigate statistical measures to differentiate normal and abnormal images. The proposed technique consists of two main stages, namely, feature extraction and classification. Primarily, 32 features incorporating four statistical measures (contrast, correlation, homogeneity and energy) calculated from co-occurrence metrics were computed. Then, mutual information was used to select features with maximal dependence on the target class and with minimal redundancy between features. Finally, a trained classifier, adaptive neuro-fuzzy interface system was implemented to classify endoscopic images into tumor, healthy and unhealthy classes. Classification accuracy of 94.2% was obtained using the proposed pipeline. Such techniques are valuable for accurate detection characterization and interpretation of endoscopic images.     

Autonomous telemetric capsule to explore the small bowel

An intestinal telemetric capsule has been developed to study the small bowel in man. It consists of a cylinder (11 mm in diameter and 39 mm in length) containing a location detector, a radiotransmitter, a lithium battery and an interchangeable tip. After having been swallowed by the patient, the capsule passes through the whole gut and is recovered in the stools. During the transit through the small bowel, the information provided by the radiotransmitter allows continuous monitoring of the distance covered from the pylorus, the direction and the velocity of progression. Moreover, according to the type of interchangeable tip, it is possible, by remote control, to sample 0.5 ml of intraluminal fluid for subsequent analysis or to release 1 ml of any liquid substance in a precisely determined place for pharmacological studies. The main originality of the capsule is its ability to transmit its precise location inside the small bowel.