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Color Laparoscopic Image Diagnosis for Automatic Detection of Coded Defect Region
Abstract
In this paper, first, we generated medical images cut as frame still image from laparoscopic video acquired by endoscopy. Using these images, we processed to encode and decode by H.265/HEVC in certain image regions, and we generated evaluation images. Next, we evaluated objectively seeing from the coded image quality by using PSNR (Peak Signal to Noise Ratio), considering the automatic detection of coded defect region information. Furthermore, we analyzed for color information by measuring both the luminance using S-CIELAB color space and the color difference using CIEDE2000. Finally, we try to classify effectively using Support Vector Machine (SVM), and we discussed including the automatic detection of coded defect region information whether it is possible for application of medical image diagnosis or not.
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The emerging need for the current medical devices to achieve immediate visualization and performing diagnostic imaging at real time augurs the demand for high computational power of the associated electronic circuitry. The demand for such a high computational requirement is often met by using software methods to accelerate the computation which is possible only to a certain extent, impairing the feasibility of real time imaging and diagnosis. In this paper, a new method of using Digital Signal Processors (DSP) with a specialized Pipelined Vision Processor (PVP) embedded at the hardware level to accelerate the routinely time consuming imaging computation is proposed and validated. A lab prototype is built for the feasibility study and clinical validation of the proposed technique. This unique architecture of the PVP in a dual core Digital Signal Processor offers a high performance accelerated framework along with it’s large on chip memory resources and reduced bandwidth requirement provides as an ideal architecture for reliable medical computational needs. We have taken two sets sample studies from SPECT for validation – 27 cases of Thyroid Medical History and 20 cases of Glomerular Filtration Rate of Kidneys. The results were compared to definitive post scan SIEMENS image analysis software. From the statistical results, it is clearly shown that, this method achieved very superior accuracy and 250% acceleration of computational speed. OAPA
Lossy image compression is increasingly used in medical applications , but great care must be taken to ensure that no diagnostically relevant features are altered. Guidelines based on compression ratios are often use to mitigate this issue, but are criticized due to the considerable compressibility variations between images. Objective image quality assessment metrics should be used instead, but the most common, mean squared error, is known to be poorly correlated with our perception of quality. Structural similarity (SSIM) is probably currently the most popular alternative, but it is also increasingly criticized. Using computed tomography simulations, this paper shows some of the limitations of SSIM when used with medical images : uniform pooling, distortion underestimation near hard edges, instabilities in regions of low variance and insensitivity in regions high intensities. Furthermore, this paper demonstrates the effect of these limitations when SSIM is used to bound compression in a block coder such as JPEG 2000.
We propose a fast stereo matching algorithm for D reconstruction of internal organs using a stereoscopic laparoscope. Stoyanov et al. have proposed a technique for recovering the 3D depth of internal organs from images taken by a stereoscopic laparoscope. In their technique, the dense stereo correspondence is solved by registration of the entire image. However, the computational cost is very high because registration of the entire image requires multidimensional optimization. In this paper, we propose a new algorithm based on a local area registration method that requires only low-dimensional optimization for reduction of computational cost. We evaluated the computational cost of the proposed algorithm using a stereoscopic laparoscope. We also evaluated the accuracy of the proposed algorithm using three types of images of abdominal models taken by a 3D laser scanner. In the matching step, the size of the template used to calculate the correlation coefficient, on which the computational cost is strongly dependent, was reduced by a factor of 16 as compared with the conventional algorithm. On the other hand, the average depth errors were 4.68 mm, 7.18 mm, and 7.44 mm respectively, and accuracy was approximately as same as the conventional algorithm.
Up to now, the diagnostic imaging was carried out based on manual handling by professional doctors and health care workers. However, it is enable to diagnose images automatically by development of the computer systems. Therefore, it is required for approach from information science and engineering fields. For generating multi-view 3D images, if we are able to support whether workers are able to use correctly or not, and if the coded defect detection and restoration for their images are possible, we consider possibility towards medical applications in the near future. In this paper, first, we diagnosed automatically for multi-view 3D images in the case of occurring defect by encoded and decoded degradation at all or certain viewpoints by H.265/HEVC. Next, we assessed and estimated quantitatively in terms of the coded image quality in order to clarify how we are able to detect the coded defect.
In this paper, we assessed subjective quality of 3D CG images by H.265/HEVC with both multi-view parallax barrier and 5K high-definition retina, and then, we analyzed them, and classified by Support Vector Machine. Next, we assessed objective quality by measuring luminance by S-CIELAB color space, and color difference by CIEDE2000.
Previously, it is not obvious to what extent was accepted for the assessors when we see the 3D image (including multi-view 3D) which the luminance change may affect the stereoscopic effect and assessment generally. We think that we can conduct a general evaluation, along with a subjective evaluation, of the luminance component using both the S-CIELAB color space and CIEDE2000. In this study, first, we performed three types of subjective evaluation experiments for contrast enhancement in an image by using the eight viewpoints parallax barrier method. Next, we analyzed the results statistically by using a support vector machine (SVM). Further, we objectively evaluated the luminance value measurement by using CIEDE2000 in the S-CIELAB color space. Then, we checked whether the objective evaluation value was related to the subjective evaluation value. From results, we were able to see the characteristic relationship between subjective assessment and objective assessment.
Recently, the use of 3D video systems without glasses has increased, and therefore 3D image quality and presence evaluation is important. There are various stereo-logical image quality evaluation methods for multi-view 3D systems without glasses. However, there is no uniform method for evaluating 3D video systems. In this study, we focus on camera interval and JPEG coding degradation with a multi-view 3D system. Previously, many studies have examined camera interval or JPEG coding degradation with 3D glasses or the binocular method. In such systems, viewers perceive stereoscopic and depth effects. Moreover, they can see from different angles, increasing viewpoints with multi-view 3D systems. However, viewers feel discomfort when changing their viewpoint. Hence, we consider, in particular, the accommodation of the camera interval and JPEG coding degradation while changing viewpoints. We have performed subjective evaluations using the absolute category rating system to assess the effects of changing the camera interval of 3D CG images or video content using an 8 viewpoint lenticular lens method. We measure assessors' ability to identify the degree of the camera interval. We analyze the results of our subjective evaluations statistically and discuss the results. Using the optimal camera interval, we perform a subjective quality evaluation employing the double stimulus impairment scale to determine assessors' ability to identify JPEG coding degradation by degree. The experimental results of this subjective evaluation are also statistically analyzed.
In this paper, we experimented the subjective evaluation for 3D CG image including the gray scale region with 8 viewpoints parallax barrier method, and we analyzed this result statistically. Next, we measured about the relation between the luminance change and the color difference by using S-CIELAB color space and CIEDE2000. As a result, we obtained knowledge about the relation among the coded image quality, the contrast enhancement, and gray scale.
Purpose:
Knowledge of the specific anatomical information of a patient is important when planning and undertaking laparoscopic surgery due to the restricted field of view and lack of tactile feedback compared to open surgery. To assist this type of surgery, we have developed a surgical navigation system that presents the patient's anatomical information synchronized with the laparoscope position. This paper presents the surgical navigation system and its clinical application to laparoscopic gastrectomy for gastric cancer.
Methods:
The proposed surgical navigation system generates virtual laparoscopic views corresponding to the laparoscope position recorded with a three-dimensional (3D) positional tracker. The virtual laparoscopic views are generated from preoperative CT images. A point-based registration aligns coordinate systems between the patient's anatomy and image coordinates. The proposed navigation system is able to display the virtual laparoscopic views using the registration result during surgery.
Results:
We performed surgical navigation during laparoscopic gastrectomy in 23 cases. The navigation system was able to present the virtual laparoscopic views in synchronization with the laparoscopic position. The fiducial registration error was calculated in all 23 cases, and the average was 14.0 mm (range 6.1-29.8).
Conclusion:
The proposed surgical navigation system can provide CT-derived patient anatomy aligned to the laparoscopic view in real time during surgery. This system enables accurate identification of vascular anatomy as a guide to vessel clamping prior to total or partial gastrectomy.
Many previous studies on image quality assessment of 3D still images or video clips have been conducted. In particular, it is important to know the region in which assessors are interested or on which they focus in images or video clips, as represented by the ROI (Region of Interest). For multi-view 3D images, it is obvious that there are a number of viewpoints; however, it is not clear whether assessors focus on objects or background regions. It is also not clear on what assessors focus depending on whether the background region is colored or gray scale. Furthermore, while case studies on coded degradation in 2D or binocular stereoscopic videos have been conducted, no such case studies on multi-view 3D videos exist, and therefore, no results are available for coded degradation according to the object or background region in multi-view 3D images. In addition, in the case where the background region is gray scale or not, it was not revealed that there were affection for gaze point environment of assessors and subjective image quality. In this study, we conducted experiments on the subjective evaluation of the assessor in the case of coded degradation by JPEG coding of the background or object or both in 3D CG images using an eight viewpoint parallax barrier method. Then, we analyzed the results statistically and classified the evaluation scores using an SVM.
Recent work in color difference has led to the recommendation of CIEDE2000 for use as an industrial color difference equation. While CIEDE2000 was designed for predicting the visual difference for large isolated patches, it is often desired to determine the perceived difference of color images. The CIE TC8-02 has been formed to examine these differences. This paper presents an overview of spatial filtering combined with CIEDE2000, to assist TC8-02 in the evaluation and implementation of an image color difference metric. Based on the S-CIELAB spatial extension, the objective is to provide a single reference for researchers desiring to utilize this technique. A general overview of how S-CIELAB functions, as well as a comparison between spatial domain and frequency domain filtering is provided. A reference comparison between three CIE recommended color difference formulae is also provided. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 425–435, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10195
Digital formatted imaging examinations are considered and their advantages over conventional methods emphasized. One display technique, the three-dimensional rendering of solid surfaces of multiple objects, is examined, and a large number of Computerized Tomography (CT) data applications is completed, where the heuristic reconstruction algorithm performs on a visual par with the optimal algorithm of Fuchs et al. The optimal algorithm, however, is much slower than the heuristic algorithm; furthermore, it requires much greater storage. The quantitative aspects of these algorithms, namely the polyhedral surface area and volume, show virtually no difference in the many cases in which comparisons are made.
Improvement of Laparoscopic Color Image Diagnosis for Automatic Detection of Coded Defect Region and Application of Effective Classifier Parameter
- N Kawabata
- T Nakaguchi
N. Kawabata and T. Nakaguchi: "Improvement of Laparoscopic Color Image Diagnosis for
Automatic Detection of Coded Defect Region and Application of Effective Classifier
Parameter," IEICE Tech. Rep., MI2018-42, MICT2018-42, pp.21--26, November 2018 (in
Japanese).