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Biomedical subjects

F F Yin

Publications and source records attributed to F F Yin.

At least 19 recordsLinked to original sources
PubMed2000

Adaptive portal CT reconstruction: a simulation study.

In radiotherapy, radiation treatment beams contain valuable information for patient setup verification. These beams may be used for portal CT reconstruction. However, direct use of the beam data for reconstruction may yield inadequate CT images simply because these beams cover only a part of the patient body. In this study, we use the treatment beams in addition to a set of regular CT projection beams to reconstruct a locally enhanced portal CT image. This approach is called adaptive portal CT reconstruction. A computer simulation demonstrated the advantages of the approach. The image reconstruction was carried out by the multilevel scheme algebraic reconstruction technique. Results indicated that the image quality of adaptive portal CT reconstruction is equivalent to that obtained from a full set of projections. This proposed technique should be not only valuable for three-dimensional radiotherapy verification, but also applicable to diagnostic CT imaging.

Computer Simulation↗
PubMed2000

Optimization of inverse treatment planning using a fuzzy weight function.

A fuzzy approach has been applied to inverse treatment planning optimization in radiation therapy. The proposed inverse-planning algorithm optimizes both the intensity-modulated beam (IMB) and the normal tissue prescription. In the IMB optimization, we developed a fast-monotonic-descent (FMD) method that has the property of fast and monotonic convergence to the minimum for a constrained quadratic objective function. In addition, a fuzzy weight function is employed to express the vague knowledge about the importance of matching the calculated dose to the prescribed dose in the normal tissue. Then, a validity function is established to optimize the normal tissue prescription. The performance of this new fuzzy prescription algorithm has been compared to that based on hard prescription methods for two treatment geometries. The FMD method presented here both provides a full-analytical solution to the optimization of intensity-modulated beams, and guarantees fast and monotonic convergence to the minimum. It has been shown that the fuzzy inverse planning technique is capable of achieving an optimal balance between the objective of matching the calculated dose to the prescribed dose for the target volume and the objective of minimizing the normal tissue dose.

Algorithms↗
PubMed1999

Structures of yeast vesicle trafficking proteins.

In protein transport between organelles, interactions of v- and t-SNARE proteins are required for fusion of protein-containing vesicles with appropriate target compartments. Mammalian SNARE proteins have been observed to interact with NSF and SNAP, and yeast SNAREs with yeast homologues of NSF and SNAP proteins. This observation led to the hypothesis that, despite low sequence homology, SNARE proteins are structurally similar among eukaryotes. SNARE proteins can be classified into two groups depending on whether they interact with SNARE binding partners via conserved glutamine (Q-SNAREs) or arginine (R-SNAREs). Much of the published structural data available is for SNAREs involved in exocytosis (either in yeast or synaptic vesicles). This paper describes circular dichroism, Fourier transform infrared spectroscopy, and dynamic light scattering data for a set of yeast v- and t-SNARE proteins, Vti1p and Pep12p, that are Q-SNAREs involved in intracellular trafficking. Our results suggest that the secondary structure of Vti1p is highly alpha-helical and that Vti1p forms multimers under a variety of solution conditions. In these respects, Vti1p appears to be distinct from R-SNARE proteins characterized previously. The alpha-helicity of Vti1p is similar to that of Q-SNARE proteins characterized previously. Pep12p, a Q-SNARE, is highly alpha-helical. It is distinct from other Q-SNAREs in that it forms dimers under many of the solution conditions tested in our experiments. The results presented in this paper are among the first to suggest heterogeneity in the functioning of SNARE complexes.

Amino Acid Sequence↗
PubMed1999

Treatment field shape verification using elliptic Fourier transform.

An automated field shape correlation technique based on elliptic Fourier transform (EFT) is developed to verify the radiation treatment field in digital portal images. In this method, the edge of the treatment field is initially extracted from the portal image and is then approximated by a polygon. The polygon is further represented with elliptic Fourier coefficients. The invariants to shift, rotation, and scale are computed from the elliptic Fourier coefficients to characterize the genuine shape feature and are used to match the reference treatment field. Invariants calculated from both test and reference field shapes are compared to determine the similarity between two treatment fields. The proposed procedure uses the first approved field shape as the reference for automated comparison with subsequent portal images. This technique not only verifies the shape of each portal field but also provides information about relative shift, rotation, and scale. A set of generic shapes is simulated to test the robustness of the algorithm and to determine the parameters used in the decision procedure. Experimental results on the simulated shapes show that this method can detect shape distortions of 2% in area and the standard deviations are 0 for shifting, 0.24 degrees for rotation, and 0.0031 for scaling. Preliminary tests on clinical portal images indicated that this technique is potentially useful for automated real-time portal verification.

Algorithms↗
PubMed1998

MR image-guided portal verification for brain treatment field.

PURPOSE: To investigate a method for the generation of digitally reconstructed radiographs directly from MR images (DRR-MRI) to guide a computerized portal verification procedure. METHODS AND MATERIALS: Several major steps were developed to perform an MR image-guided portal verification procedure. Initially, a wavelet-based multiresolution adaptive thresholding method was used to segment the skin slice-by-slice in MR brain axial images. Some selected anatomical structures, such as target volume and critical organs, were then manually identified and were reassigned to relatively higher intensities. Interslice information was interpolated with a directional method to achieve comparable display resolution in three dimensions. Next, a ray-tracing method was used to generate a DRR-MRI image at the planned treatment position, and the ray tracing was simply performed on summation of voxels along the ray. The skin and its relative positions were also projected to the DRR-MRI and were used to guide the search of similar features in the portal image. A Canny edge detector was used to enhance the brain contour in both portal and simulation images. The skin in the brain portal image was then extracted using a knowledge-based searching technique. Finally, a Chamfer matching technique was used to correlate features between DRR-MRI and portal image. RESULTS: The MR image-guided portal verification method was evaluated using a brain phantom case and a clinical patient case. Both DRR-CT and DRR-MRI were generated using CT and MR phantom images with the same beam orientation and then compared. The matching result indicated that the maximum deviation of internal structures was less than 1 mm. The segmented results for brain MR slice images indicated that a wavelet-based image segmentation technique provided a reasonable estimation for the brain skin. For the clinical patient case with a given portal field, the MR image-guided verification method provided an excellent match between features in both DRR-MRI and portal image. Moreover, target volume could be accurately visualized in the DRR-MRI and mapped over to the corresponding portal image for treatment verification. The accuracy of DRR-MRI was also examined by comparing it to the corresponding simulation image. The matching results indicated that the maximum deviation of anatomical features was less than 2.5 mm. CONCLUSION: A method for MR image-guided portal verification of brain treatment field was developed. Although the radiographic appearance in the DRR-MRI is different from that in the portal image, DRR-MRI provides essential anatomical features (landmarks and target volume) as well as their relative locations to be used as references for computerized portal verification.

Brain Neoplasms↗
PubMed1997

Oncologic image compression using both wavelet and masking techniques.

A new algorithm has been developed to compress oncologic images using both wavelet transform and field masking methods. A compactly supported wavelet transform is used to decompose the original image into high- and low-frequency subband images. The region-of-interest (ROI) inside an image, such as an irradiated field in an electronic portal image, is identified using an image segmentation technique and is then used to generate a mask. The wavelet transform coefficients outside the mask region are then ignored so that these coefficients can be efficiently coded to minimize the image redundancy. In this study, an adaptive uniform scalar quantization method and Huffman coding with a fixed code book are employed in subsequent compression procedures. Three types of typical oncologic images are tested for compression using this new algorithm: CT, MRI, and electronic portal images with 256 x 256 matrix size and 8-bit gray levels. Peak signal-to-noise ratio (PSNR) is used to evaluate the quality of reconstructed image. Effects of masking and image quality on compression ratio are illustrated. Compression ratios obtained using wavelet transform with and without masking for the same PSNR are compared for all types of images. The addition of masking shows an increase of compression ratio by a factor of greater than 1.5. The effect of masking on the compression ratio depends on image type and anatomical site. A compression ratio of greater than 5 can be achieved for a lossless compression of various oncologic images with respect to the region inside the mask. Examples of reconstructed images with compression ratio greater than 50 are shown.

Algorithms↗
PubMed1996

An observer study for direct comparison of clinical efficacy of electronic to film portal images.

PURPOSE: To directly compare clinical efficacy of electronic to film portal images. METHODS AND MATERIALS: An observer study was designed to compare clinical efficacy of electronic to film portal images acquired using a liquid matrix ion-chamber electronic portal imaging device and a conventional metal screen/film system. Both images were acquired simultaneously for each treatment port and the electronic portal images were printed on gray-level thermal paper. Four radiation oncologists served as observers and evaluated a total of 44 sets of images for four different treatment sites: lung, pelvis, brain, and head/neck. Each set of images included a simulation image, a double-exposure portal film, and video paper prints of electronic portal images. Eight to nine anatomical landmarks were selected from each treatment site. Each observer was asked to rate each landmark in terms of its clinical visibility and to rate the ease of making the pertinent verification decision in the corresponding electronic and film portal images with the aid of the simulation image. RESULTS: Ratings for the visibility of landmarks and for the verification decision of treatment ports were similar for electronic and film images for most landmarks. However, vertebral bodies and several landmarks in the pelvis such as the acetabulum and public symphysis were more visible in the portal film images than in the electronic portal images. CONCLUSION: The visibility of landmarks in electronic portal images is comparable to that in film portal images. Verification of treatment ports based only on electronic portal images acquired using an electronic portal imaging device is generally achievable.

Observer Variation↗
PubMed1996

The effect of detector size to the broadening of the penumbra--a computer simulated study.

The effect of detector size to the broadening of the measured beam penumbra has been a subject of numerous studies. Based on measured data, linear and quadratic curves have been proposed to describe the relationship between the measured penumbra width, between 10%-90% and 20%-80% intensities, and the detector size. Extrapolations of these curves to zero detector size also suggest that the inherent penumbras can be deduced. However, due to experimental noise, especially when a small ionization chamber is used, and the inherent penumbra is not known, it is difficult to discern the superiority of either model. In this study, one dimensional convolution using a thin circular disk shape detector was employed to analyze the effect of detector size to the broadening of the penumbra. A set of beams with different inherent penumbra widths, ranging from 0 to 350 in arbitrary unit, was first generated. Each beam was then convoluted with the response function of the detectors with different sizes from 10 to 280, in arbitrary unit. The result is an output signal with penumbra that is wider than the inherent penumbra. The plots of penumbra widths to detector radii are a family of concave parabolic curves with different inherent penumbra widths. The concave portions of the curve represent results from scanning with detectors equal to or smaller than the penumbra width, and the linear portions represent results from scanning with detectors much larger than the penumbra. The curves are nothing but different scales of one curve. The extrapolations of the curves to the penumbra axis when the detector radius approaches zero give the deduced inherent penumbra widths. The deduced inherent penumbra widths approximate the inherent penumbra widths satisfactorily. From the graphs provided, the inherent penumbra can be deduced using the detector radius and the measured penumbra width.

Computer Simulation↗
PubMed1994

Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques.

Mammographic screening of asymptomatic women has shown effectiveness in the reduction of breast cancer mortality. We are developing a computerized scheme for the detection of mammographic masses as an aid to radiologists in mammographic screening programs. Possible masses on digitized screen/film mammograms are initially identified using a nonlinear bilateral-subtraction technique, which is based on asymmetric density patterns occurring in corresponding portions of right and left mammograms. In this study, we analyze the characteristics of actual masses and nonmass detections to develop feature-analysis techniques with which to reduce the number of nonmass (ie, false-positive) detections. These feature-analysis techniques involve (1) the extraction of various features (such as area, contrast, circularity and border-distance based on the density and geometric information of masses in both processed, and original breast images), and (2) tests of the extracted features to reduce nonmass detections. Cumulative histograms of both actual-mass detections and nonmass detections are used to characterize extracted features and to determine the cutoff values used in the feature tests. The effectiveness of the feature-analysis techniques is evaluated in combination with the computerized detection scheme that uses the nonlinear bilateral-subtraction technique using free-response receiver operating characteristic analysis and 77 patient cases (308 mammograms). Results show that the feature-analysis techniques effectively improve the performance of the computerized detection scheme: about 35% false-positive detections were eliminated without loss in sensitivity when the feature-analysis techniques were used.

Breast Neoplasms↗
PubMed1994

Input/output characteristics of a matrix ion-chamber electronic portal imaging device.

The input/output characteristics of a matrix liquid ion-chamber electronic portal imaging device (EPID) are investigated to elucidate the imaging properties of EPIDs. The radiation input to the detector, represented by dose rate, and the pixel value output from the device are related by a characteristic curve. Various incident radiation intensities are obtained by changing the source-to-detector distance (SDD). For each incident radiation intensity, an electronic portal image is obtained using a field size of 5 x 5 cm2. The output pixel value of the EPID is represented by the average pixel value of a region of interest of 9 x 9 pixels centered at a selected point. The effects of various accelerator settings, such as the repetition-rate setting and photon energy, gantry angle, field size, SDD, and acquisition mode of the EPID on characteristic curves are investigated at the central axis. The off-axis response of the detector is also examined. The derivative of the pixel value with respect to the input dose rate is used to analyze the detector contrast. Results indicate that the output pixel value is not a linear function of the incident radiation intensity. The detector contrast is comparable between photon energies of 10 and 6 MV and increases at low dose rates. The response of the imaging device varies substantially with acquisition mode, but is less sensitive to the SDD used for calibration. Characteristic curves are consistent for different gantry angles at the central axis and with the off-axis locations when the gantry angle is used for imaging and calibration, but vary with off-axis locations when the gantry angle is not at the calibration direction. Characteristic curves are also found to vary with different field sizes, but are similar in shape.

Humans↗
PubMed1994

A technique of automating compensator design for lung inhomogeneity correction using an electron portal imaging device.

A technique of automating compensator design for lung inhomogeneity correction using an electron portal imaging device (EPID) has been investigated. This technique utilizes exit-radiation information as detected by an EPID to determine the thickness of the compensator desired. In this particular study, the compensator thickness is determined to provide a uniform gray-level distribution (related to uniform exit-dose distribution) in the region of the portal image to be compensated. Initially, a compensation characteristic curve, which relates the compensator thickness to the pixel value of the electronic portal image, is measured for both the Lead and Lipowitz compensator materials and a 6-MV photon beam. Then, a chest-treatment field is simulated using an anthropomorphic phantom. Based on the analysis of the profile (gray-level distribution) across the lung and mediastinum regions in the electronic portal image, the average of pixel values within the mediastinum region is selected as the matching level and the regions to be compensated are determined. With the aid of the predetermined compensation characteristic curve and proper distance scaling, the compensator thickness at each pixel location is automatically calculated at the block tray level to correct lung inhomogeneity. In a simple test using a single anterioposterior (AP) chest field, the compensated profile in the electronic portal image presents a uniform gray-level distribution (related to uniform exit dose) compared to the uncompensated profile.(ABSTRACT TRUNCATED AT 250 WORDS)

Biophysical Phenomena↗
PubMed1994

Effect of case selection on the performance of computer-aided detection schemes.

The choice of clinical cases used to train and test a computer-aided diagnosis (CAD) scheme can affect the test results (i.e., error rate). In this study, we deliberately modified the components of our testing database to study the effects of this modification on measured performance. Using a computerized scheme for the automated detection of breast masses from mammograms, it was found that the sensitivity of the scheme ranged between 26% and 100% (at a false positive rate of 1.0 per image) depending on the cases used to test the scheme. Even a 20% change in the cases comprising the database can reduce the measured sensitivity by 15%-25%. Because of the strong dependence of measured performance on the testing database, it is difficult to estimate reliably the accuracy of a CAD scheme. Furthermore, it is questionable to compare different CAD schemes when different cases are used for testing. Sharing databases, creating a common database, or using a quantitative measure to characterize databases are possible solutions to this problem. However, none of these solutions exists or is practiced at present. Therefore, as a short-term solution, it is recommended that the method used for selecting cases, and histograms or mean and standard deviations of relevant image features be reported whenever performance data are presented.

Breast Neoplasms↗
PubMed1994

Computerized detection of masses in digital mammograms: automated alignment of breast images and its effect on bilateral-subtraction technique.

An automated technique for the alignment of right and left breast images has been developed for use in the computerized analysis of bilateral breast images. In this technique, the breast region is first identified in each digital mammogram by use of histogram analysis and morphological filtering operations. The anterior portions of the tracked breast border and computer-identified nipple positions are selected as landmarks for use in image registration. The paired right and left breast images, either from mediolateral oblique or craniocaudal views, are then registered relative to each other by use of a least-squares matching method. This automated alignment technique has been applied to our computerized detection scheme that employs a nonlinear bilateral-subtraction method for the initial identification of possible masses. The effectiveness of using bilateral subtraction in identifying asymmetries between corresponding right and left breast images is examined by comparing detection performances obtained with various computer-simulated misalignments of 40 pairs of clinical mammograms. Based on free-response receiver operating characteristic and regression analyses, the detection performance obtained with the automated alignment technique was found to be higher than that obtained with simulated misalignments. Detection performance decreased gradually as the amount of simulated misalignment increased. These results indicate that automatic alignment of breast images is possible and that mass-detection performance appears to improve with the inclusion of asymmetric anatomic information but is not sensitive to slight misalignment.

Breast Neoplasms↗
PubMed1993

Comparison of bilateral-subtraction and single-image processing techniques in the computerized detection of mammographic masses.

RATIONALE AND OBJECTIVES: Identification of regions as possible masses on digitized screen film mammograms is an important initial step in the computerized detection of breast carcinomas. Possible masses may be initially extracted using criteria based on optical densities, geometric patterns, and asymmetries between corresponding locations in right and left mammograms. In this study, the usefulness of information arising from mammographic asymmetries for the identification of mass lesions is investigated. METHODS: Two techniques are investigated--a nonlinear bilateral-subtraction technique based on image pairs and a local gray-level thresholding technique based on single images. Detection performances obtained with the two techniques in combination with various feature-analysis techniques are evaluated using 154 pairs of mammograms and compared using free-response receiver operating characteristic (FROC) analysis. RESULTS: The nonlinear bilateral-subtraction technique performed better than the local gray-level thresholding technique. CONCLUSION: The incorporation of asymmetric information appears to be useful for computerized identification of possible masses on mammograms.

Female↗
PubMed1992

Evaluation of imaging properties of a laser film digitizer.

In this paper we provide a quantitative assessment of the basic imaging properties of a laser film digitizer. The characteristic curve of the digitizer was determined in terms of the relationship between input optical density and output pixel value. Spatial resolution of the laser digitizer was characterized using the presampling modulation transfer function (MTF), which was measured using a curve fitting technique with an angulated slit. For the noise analysis, we compared the Wiener spectra of uniformly exposed film samples before and after digitization. The effects of different sampling distances and scanning directions were investigated. Our results show that the characteristic curve of the laser digitizer was linear. The presampling MTFs of the digitizer were similar at different sampling distances and were substantially greater in the vertical scanning direction than in the horizontal direction. The noise of the digitized film sample was mainly affected by the presampling MTF and structure noise of the digitizer.

Evaluation Studies as Topic↗
PubMed1991

Direct comparison of conventional and computed radiography with a dual-image recording technique.

To compare the image quality of computed radiographic (CR) with conventional screen-film images, the authors used a dual-image recording technique. Images were simultaneously acquired with a conventional screen-film combination and a storage-phosphor imaging plate loaded into a single cassette. Wiener spectra and modulation transfer function were compared for both image types. A preliminary observer performance test was conducted with chest images obtained with the dual-image recording technique on portable and fixed equipment. Analysis of physical parameters and observer test results suggests that the conventional screen-film system can provide slightly superior image quality, although the CR system has some advantage in bedside applications.

Confidence Intervals↗
PubMed1991

Data compression: effect on diagnostic accuracy in digital chest radiography.

High-resolution digital images make up very large data sets that are relatively slow to transmit and expensive to store. Data compression techniques are being developed to address this problem, but significant image deterioration can occur at high compression ratios. In this study, the authors evaluated a form of adaptive block cosine transform coding, a new compression technique that allows considerable compression of digital radiographs with minimal degradation of image quality. To determine the effect of data compression on diagnostic accuracy, observer tests were performed with 60 digitized chest radiographs (2,048 x 2,048 matrix, 1,024 shades of gray) containing subtle examples of pneumothorax, interstitial infiltrate, nodules, and bone lesions. Radiographs with no compression, with 25:1 compression, and with 50:1 compression ratios were presented in randomized order to 12 radiologists. The results suggest that, with this compression scheme, compression ratios as high as 25:1 may be acceptable for primary diagnosis in chest radiology.

Humans↗