Investigation of the lineâ pair pattern method for evaluating mammographic focal spot performance

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135107/1/mp7921.pd

Quantitative CT of lung nodules: Dependence of calibration on patient body size, anatomic region, and calibration nodule size for singleâ and dualâ energy techniques

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134901/1/mp8536.pd

Real‐time B‐mode ultrasound quality control test procedures. Report of AAPM Ultrasound Task Group No. 1

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134873/1/mp8404.pd

A comparative study of limitedâ angle coneâ beam reconstruction methods for breast tomosynthesis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134781/1/mp7543.pd

Accuracy of the CT numbers of simulated lung nodules imaged with multiâ detector CT scanners

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135050/1/mp9332.pd

Classification of compressed breast shapes for the design of equalization filters in xâ ray mammography

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134971/1/mp8272.pd

Local Compression in Automated Breast Ultrasound in the Mammographic Geometry

Background, Motivation and Objective: Automated ultrasound scanning (AUS) of the breast has developed more slowly than anticipated. The main limitation, beyond achieving adequate acoustic coupling to the breast, has been excessive shadow artifacts, as reflecting structures at acute angles to the ultrasound beam are not flattened by the transducer as well as in manual scanning. We believe that imaging of the breast in near mammographic compression provides much of the needed flattening. The question under initial study in this effort is, whether in breast AUS under very light mammographic compression, local compression by the transducer might flatten the acutely oriented structures further and reduce the acoustic path length to key structures in the breast. We suspect these improvements will be possible without distorting the breast so dramatically that the lesion registration advantages of scanning the breast in the same system as mammography or digital breast tomosynthesis (DBT) are not realized. Preliminary tests are reported here, as well as design of a system for a more refined human study. Statement of Contribution/Methods: Initial imaging tests were performed in our combined AUS/DBT system. A fiber mesh, loosened slightly in its frame, replaced the standard plastic mammography compression paddle. The transducer, in contact with the mesh and the breast, was translated by motors. The compression force of the linear array transducer on its vertical was manually controlled. Breast phantoms and the breasts of three women were scanned with usual compression by the mesh paddle and then with less global, but added local, compression. Results: Examples of flattened structures were observed more brightly in the locally compressed breasts, and acoustic paths longer than 35 mm were reduced, by _10 mm. In many areas image penetration was 3 cm greater. In one case, image volumes w/wo local compression were spatially aligned by nonlinear image registration software. - - Discussion and Conclusions: Visual indicators of image features expected to provide improved ultrasonic imaging were observed with local compression and lateral movement of tissues appeared acceptable. These results motivated design and construction of an apparatus to make local compression practical and safe. It utilizes joystick control of the vertical compression force during scanning, realized by pneumatic actuators attached to the transducer. The air pressure applied to these actuators is also applied to actuators in the joystick for force feedback to the operator. Two miniature vibrators attached to the joystick provide vibrotactile feedback of the reaction torques computed from the measurements of 6 force sensors on the transducer holder. The fail-safe system design insures no pneumatic compression force application to the breast in case of power loss or emergency shutdown.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87269/4/Saitou50.pd

Evaluation of dual energy quantitative CT for determining the spatial distributions of red marrow and bone for dosimetry in internal emitter radiation therapy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135113/1/mp0378.pd

Design of a high-sensitivity classifier based on a genetic algorithm: application to computer-aided diagnosis

A genetic algorithm (GA) based feature selection method was developed for the design of high-sensitivity classifiers, which were tailored to yield high sensitivity with high specificity. The fitness function of the GA was based on the receiver operating characteristic (ROC) partial area index, which is defined as the average specificity above a given sensitivity threshold. The designed GA evolved towards the selection of feature combinations which yielded high specificity in the high-sensitivity region of the ROC curve, regardless of the performance at low sensitivity. This is a desirable quality of a classifier used for breast lesion characterization, since the focus in breast lesion characterization is to diagnose correctly as many benign lesions as possible without missing malignancies. The high-sensitivity classifier, formulated as the Fisher's linear discriminant using GA-selected feature variables, was employed to classify 255 biopsy-proven mammographic masses as malignant or benign. The mammograms were digitized at a pixel size of mm, and regions of interest (ROIs) containing the biopsied masses were extracted by an experienced radiologist. A recently developed image transformation technique, referred to as the rubber-band straightening transform, was applied to the ROIs. Texture features extracted from the spatial grey-level dependence and run-length statistics matrices of the transformed ROIs were used to distinguish malignant and benign masses. The classification accuracy of the high-sensitivity classifier was compared with that of linear discriminant analysis with stepwise feature selection . With proper GA training, the ROC partial area of the high-sensitivity classifier above a true-positive fraction of 0.95 was significantly larger than that of , although the latter provided a higher total area under the ROC curve. By setting an appropriate decision threshold, the high-sensitivity classifier and correctly identified 61% and 34% of the benign masses respectively without missing any malignant masses. Our results show that the choice of the feature selection technique is important in computer-aided diagnosis, and that the GA may be a useful tool for designing classifiers for lesion characterization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48962/2/m81014.pd

Effect of a Gel Retainment Dam on Automated Ultrasound Coverage in a Dual‐Modality Breast Imaging System

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135299/1/jum20102971075.pd