Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

Comparison of Preoperative Nd:YAG Laser Anterior Capsulotomy Versus Two-Stage Curvilinear Capsulorhexis in Phacoemulsification of White Intumescent Cataracts

BACKGROUND AND OBJECTIVE: To compare the results of preoperative Nd:YAG laser anterior capsulotomy versus two-stage continuous curvilinear capsulorhexis (CCC) in phacoemulsification of eyes with white intumescent cataracts and liquefied cortex. PATIENTS AND METHODS: Twenty-three eyes with white intumescent cataract were consecutively randomized for phacoemulsification with preoperative Nd:YAG laser anterior capsulotomy (group 1, n = 11) or two-stage CCC (group 2, n = 12) procedures. Intraoperative findings and postoperative outcomes were compared using the nonparametric tests. RESULTS: Postoperative Visual acuity, mean surgical time, mean effective phacoemulsification time, and frequency of complications were not significantly different between the two groups (P > .05). Two cases in each group were converted to the extracapsular technique. Excluding these four patients, surgical time was shorter In group 1 (P = .017). CONCLUSION: Preoperative Nd:YAG laser anterior capsulotomy is a safe technique in decompressing the capsular bag before phacoemulsification of white intumescent cataracts with liquefied cortex.

Short communication: Identification of subclinical cow mastitis pathogens in milk by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Subclinical mastitis is a common and easily disseminated disease in dairy herds. Its routine diagnosis via bacterial culture and biochemical identification is a difficult and time-consuming process. In this work, we show that matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) allows bacterial identification with high confidence and speed (1 d for bacterial growth and analysis). With the use of MALDI-TOF MS, 33 bacterial culture isolates from milk of different dairy cows from several farms were analyzed, and the results were compared with those obtained by classical biochemical methods. This proof-of-concept case demonstrates the reliability of MALDI-TOF MS bacterial identification, and its increased selectivity as illustrated by the additional identification of coagulase-negative Staphylococcus species and mixed bacterial cultures. Matrix-assisted laser desorption-ionization mass spectrometry considerably accelerates the diagnosis of mastitis pathogens, especially in cases of subclinical mastitis. More immediate and efficient animal management strategies for mastitis and milk quality control in the dairy industry can therefore be applied.