Adaptive illumination in wireless capsule endoscopy system

Shrestha, Ravi; Zhang, Xuechao; Gias, Ziad; Wahid, Khan A.

doi:10.1109/iscas.2015.7168749

Cited by 4 publications

(7 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To evaluate the performance of the proposed algorithm, we have implemented both the old [18] and new algorithms in the experiments. As stated before, the capsule prototype captures images at the rate of 2 fps.…”

Section: Resultsmentioning

confidence: 99%

“…However, in the under-and over-saturated zones, the function is non-linear; as a result, it provides high dimming factor for very low brightness (or under-saturated region) and low dimming factor for very high brightness (or over-saturated region). This allows us to find the optimum dimming factor and hence correct the intensity of the image (or image segment) much more quickly than the uniform function used in our previous work in [18].…”

Section: Detect Brightness Level Using Sigmoid Functionmentioning

confidence: 99%

“…From the table, it is noted that the images with 75% brightness level (BL) show the best results in cases of constant brightness. The previous algorithm [18] works well in case of no ambient light; however, the presence of ambient light compromises the quality of the captured image. Now we see that the images captured using adaptive brightness have higher focus and entropy values in both cases (ambient light and no ambient light).…”

Section: A Assessment Of Image Qualitymentioning

confidence: 99%

“…At 75%, 50%, and 25% BL, the current consumption reduces to 39.1 mA, 36.5 mA, and 34.1 mA respectively. The average consumptions for both new and previous algorithms [18] for all 21 frames have been measured to be 36 mA and 39.5 mA respectively. Thus it is seen that the average consumption of the proposed adaptive brightness (AB) method is higher than 25%BL but lower than 50%BL.…”

Section: B Analysis Of Power (Or Current) Consumptionmentioning

confidence: 99%

“…So the aim is to offload the processing to the data logger or computer side keeping the frame rate high and image quality acceptable, and at the same adding no overhead in hardware and power requirement. In [18], our group suggested a simple algorithm for adjusting brightness of LED using pulse width modulation. Even though, the algorithm is adaptive in nature, it failed to provide uniform brightness when ambient light is present and the image is over-exposed.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function

Shrestha

Mohammed

Hasan

et al. 2016

IEEE Trans. Biomed. Circuits Syst.

Self Cite

View full text Add to dashboard Cite

Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Detect Brightness Level Using Sigmoid Functionmentioning

confidence: 99%

Section: A Assessment Of Image Qualitymentioning

confidence: 99%

Section: B Analysis Of Power (Or Current) Consumptionmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function

Shrestha

Mohammed

Hasan

et al. 2016

IEEE Trans. Biomed. Circuits Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

Frontiers of robotic endoscopic capsules: a review

et al. 2016

View full text Add to dashboard Cite

Digestive diseases are a major burden for society and healthcare systems, and with an aging population, the importance of their effective management will become critical. Healthcare systems worldwide already struggle to insure quality and affordability of healthcare delivery and this will be a significant challenge in the midterm future. Wireless capsule endoscopy (WCE), introduced in 2000 by Given Imaging Ltd., is an example of disruptive technology and represents an attractive alternative to traditional diagnostic techniques. WCE overcomes conventional endoscopy enabling inspection of the digestive system without discomfort or the need for sedation. Thus, it has the advantage of encouraging patients to undergo gastrointestinal (GI) tract examinations and of facilitating mass screening programmes. With the integration of further capabilities based on microrobotics, e.g. active locomotion and embedded therapeutic modules, WCE could become the key-technology for GI diagnosis and treatment. This review presents a research update on WCE and describes the state-of-the-art of current endoscopic devices with a focus on research-oriented robotic capsule endoscopes enabled by microsystem technologies. The article also presents a visionary perspective on WCE potential for screening, diagnostic and therapeutic endoscopic procedures.

show abstract