Color-to-Grayscale: Does the Method Matter in Image Recognition?

In image recognition it is often assumed the method used to convert color images to grayscale has little impact on recognition performance. We compare thirteen different grayscale algorithms with four types of image descriptors and demonstrate that this assumption is wrong: not all color-to-grayscale algorithms work equally well, even when using descriptors that are robust to changes in illumination. These methods are tested using a modern descriptor-based image recognition framework, on face, object, and texture datasets, with relatively few training instances. We identify a simple method that generally works best for face and object recognition, and two that work well for recognizing textures

Interrater and Intrarater Reliability in the Diagnosis and Staging of Endometriosis

OBJECTIVE: To estimate the interrater and intrarater reliability of endometriosis diagnosis and severity of disease among gynecologic surgeons viewing operative digital images. METHODS: The study population comprised a random sample (n = 148 [36%]) of women who participated in the Endometriosis: Natural History, Diagnosis and Outcomes study. Four academic expert and four local, specialized expert surgeons reviewed the images, diagnosed the presence or absence of endometriosis for each woman, and rated severity using the revised American Society for Reproductive Medicine (ASRM) criteria. Interrater-level and intrarater-level agreement were calculated for both endometriosis diagnosis and staging. RESULTS: The interrater reliability for endometriosis diagnosis among the eight surgeons was substantial: Fleiss kappa = 0.69 (95% confidence interval [CI] 0.64-0.74). Surgeons agreed on revised ASRM endometriosis staging criteria after experienced assessment in a majority of cases (mean 61%, range 52-75%) with moderate interrater reliability: Fleiss kappa = 0.44 (95% CI 0.41-0.47). The intrarater reliability for experienced assessment compared with computer-assisted revised ASRM staging was almost perfect (mean weighted kappa = 0.95, range 0.89-0.99). CONCLUSION: Substantial reliability was found for revised ASRM endometriosis diagnosis, whereas moderate reliability was observed for staging. Almost perfect reliability was observed for surgeons' rating of disease severity compared with computerized-assisted, checklist-based staging. Findings suggest that reliability in endometriosis diagnosis is not greatly altered by location or composition of surgeons, supporting the conduct of multisite studies or compilation of endometriosis data across clinical centers. Although surgeons appear to be skilled at assessing endometriosis stage intuitively, how staging of disease burden correlates with clinical outcomes remains to be developed. (Obstet Gynecol 2012; 120: 104-12) DOI:10.1097/AOG. 0b013e31825bc6cfKeywords: Population, American Fertility Society, System, Interobserver variability, Intraobserver, Classification, Reproducibility, Adhesions, Laparoscopy, Agreemen

Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event driven processing

This paper proposes a novel approach to anomalous behaviour detection in video. The approach is comprised of three key components. First, distributions of spatiotemporal oriented energy are used to model behaviour. This representation can capture a wide range of naturally occurring visual spacetime patterns and has not previously been applied to anomaly detection. Second, a novel method is proposed for comparing an automatically acquired model of normal behaviour with new observations. The method accounts for situations when only a subset of the model is present in the new observation, as when multiple activities are acceptable in a region yet only one is likely to be encountered at any given instant. Third, event driven processing is employed to automatically mark portions of the video stream that are most likely to contain deviations from the expected and thereby focus computational efforts. The approach has been implemented with real-time performance. Quantitative and qualitative empirical evaluation on a challenging set of natural image videos demonstrates the approach’s superior performance relative to various alternatives

Endometriosis diagnosis and staging by operating surgeon and expert review using multiple diagnostic tools: an inter-rater agreement study

OBJECTIVE: To determine agreement on endometriosis diagnosis between real-time laparoscopy and subsequent expert review of digital images, operative reports, magnetic resonance imaging (MRI), and histopathology, viewed sequentially. DESIGN: Inter-rater agreement study. SETTING: Five urban surgical centres. POPULATION: Women, aged 18-44 years, who underwent a laparoscopy regardless of clinical indication. A random sample of 105 women with and 43 women without a postoperative endometriosis diagnosis was obtained from the ENDO study. METHODS: Laparoscopies were diagnosed, digitally recorded, and reassessed. MAIN OUTCOME MEASURES: Inter-observer agreement of endometriosis diagnosis and staging according to the revised American Society for Reproductive Medicine criteria. Prevalence and bias-adjusted kappa values (κ) were calculated for diagnosis, and weighted κ values were calculated for staging. RESULTS: Surgeons and expert reviewers had substantial agreement on diagnosis and staging after viewing digital images (n = 148; mean κ = 0.67, range 0.61-0.69; mean κ = 0.64, range 0.53-0.78, respectively) and after additionally viewing operative reports (n = 148; mean κ = 0.88, range 0.85-0.89; mean κ = 0.85, range 0.84-0.86, respectively). Although additionally viewing MRI findings (n = 36) did not greatly impact agreement, agreement substantially decreased after viewing histological findings (n = 67), with expert reviewers changing their assessment from a positive to a negative diagnosis in up to 20% of cases. CONCLUSION: Although these findings suggest that misclassification bias in the diagnosis or staging of endometriosis via visualised disease is minimal, they should alert gynaecologists who review operative images in order to make decisions on endometriosis treatment that operative reports/drawings and histopathology, but not necessarily MRI, will improve their ability to make sound judgments. TWEETABLE ABSTRACT: Endometriosis diagnosis and staging agreement between expert reviewers and operating surgeons was substantial