Roger Engelmann

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This work presents the usefulness of texture features in the classification of breast lesions in 5,518 images of regions of interest, which were obtained from the Digital Database for Screening Mammography that included microcalcifications, masses, and normal cases. Sixteen texture features were used, i.e., 13 were based on the spatial gray-level dependence(More)
PURPOSE To determine the effect of computer-aided diagnosis (CAD) on the accuracy of pulmonary nodule detection. MATERIALS AND METHODS Twenty abnormal chest radiographs, each with a single nodule, and 20 normal radiographs were digitized with a laser scanner. These images were analyzed by using a computer program that indicates areas that may represent(More)
We developed an advanced computer-aided diagnostic (CAD) scheme for the detection of various types of lung nodules on chest radiographs intended for implementation in clinical situations. We used 924 digitized chest images (992 noncalcified nodules) which had a 500 x 500 matrix size with a 1024 gray scale. The images were divided randomly into two sets(More)
The authors developed a temporal subtraction scheme based on a nonlinear geometric warping technique to assist radiologists in the detection of interval changes in chest radiographs obtained on different occasions. The performance of the current temporal subtraction scheme is reasonably good; however, severe misregistration can occur in some cases. The(More)
OBJECTIVE The purpose of our study was to evaluate whether a computer-aided diagnosis (CAD) scheme can assist radiologists in distinguishing small benign from malignant lung nodules on high-resolution CT (HRCT). MATERIALS AND METHODS We developed an automated computerized scheme for determining the likelihood of malignancy of lung nodules on multiple HRCT(More)
Computer-aided diagnosis (CAD) provides a computerized diagnostic result as a " second opinion " to assist radiologists in the diagnosis of various diseases by use of medical images. CAD has become a practical clinical approach in diagnostic radiology, although, at present, primarily in the area of detection of breast cancer in mammograms. Currently, a(More)
Radiologists routinely compare multiple chest radiographs acquired from the same patient over time to more completely understand changes in anatomy and pathology. While such comparisons are achieved conventionally through a side-by-side display of images, image registration techniques have been developed to combine information from two separate radiographic(More)
In this paper, we are exploring the response of individual classifier families on imbalanced medical data. In this work we are using LIDC (Lung Image Database Consortium) dataset, which is a very good example for imbalanced data. The main objective of this work is to examine how will be the response of different categories of classifier on imbalanced(More)
In order to aid radiologists' routine work for interpreting bone scan images, we developed a computerized method for temporal subtraction (TS) images which can highlight interval changes between successive whole-body bone scans, and we performed a prospective clinical study for evaluating the clinical utility of the TS images. We developed a TS image server(More)