Channelized Hotelling observers have been evaluated in signal detection in medical images. However, these model
observers fall short of overestimate of detection performance compared with human observers. Here, we present a
modified channelized Hotelling observer with divisive normalization mechanism. In this model, images first traverse a
series of Gabor filters of different orientations, phases and spatial frequencies. Then, the channels outputs pass through a
nonlinear process and pool in several channels. Finally, these channels responses are normalized through a divisive
operation. Human performances of nodule detection in chest radiography are evaluated by 2AFC experiments. The same
detection tasks are performed by the model observers. The results show that the modified channelized Hotelling observer
can well predict the human performances.
This paper presents a statistical reconstruction algorithm for dual-energy (DE) CT of polychromatic x-ray source. Each
pixel in the imaged object is assumed to be composed of two basis materials (i.e., bone and soft tissue) and a penalizedlikelihood
objective function is developed to determine the densities of the two basis materials. Two penalty terms are
used respectively to penalize the bone density difference and the soft tissue density difference in neighboring pixels. A
gradient ascent algorithm for monochromatic objective function is modified to maximize the polychromatic penalizedlikelihood
objective function using the convexity technique. In order to reduce computation consumption, the
denominator of the update step is pre-calculated with reasonable approximation replacements. Ordered-subsets method is
applied to speed up the iteration. Computer simulation is implemented to evaluate the penalized-likelihood algorithm.
The results indicate that this statistical method yields the best quality image among the tested methods and has a good
noise property even in a lower photon count.
We aimed to evaluate the effect of different components of chest image on performances of both human observer and
channelized Fisher-Hotelling model (CFH) in nodule detection task. Irrelevant and relevant components were separated
from clinical chest radiography by employing Principal Component Analysis (PCA) methods. Human observer
performance was evaluated in two-alternative forced-choice (2AFC) on original clinical images and anatomical structure
only images obtained by PCA methods. Channelized Fisher-Hotelling model with Laguerre-Gauss basis function was
evaluated to predict human performance. We show that relevant component is the primary factor influencing on nodule
detection in chest radiography. There is obvious difference of detectability between human observer and CFH model for
nodule detection in images only containing anatomical structure. CFH model should be used more carefully.
In this paper, we propose a novel method for beam hardening correction in polychromatic transmission tomography. A
family of polynomials is firstly determined in a training phase, which forms a complete set in the sense of X-ray physics
of medical diagnostic imaging. In particular, every polynomial in the set is indexed by a beam hardening factor, i.e.
effective atomic number, which is further assigned to specific X-ray penetrating path. In order to successfully accomplish
the assignation in an imaging phase, another polynomial is adopted to formulize the mapping relationship between the
index of polynomial family and the area density ratio of bone tissue. Here, the area density ratio of bone tissue is
calculated after the pre reconstructed image being segmented into soft tissue and bone regions. The mapping polynomial
is iteratively approximated by a dedicated HL Consistency (HLC) based nonlinear algorithm. The characteristics of this
method include that the polynomial family can cover the variations of both high potential and effective filter of X-ray
tube, the beam hardening correction in the imaging phase can adapt the content variations of objects being imaged, and
the correction effect is also sophisticated even bowtie filter exists. Performance analysis and related computer simulation
show that our HLC based correction is much robust than traditional bone correction to the variants of scale factor lambda<sub>0</sub>.
In medical radiation department, physician makes his diagnosis by surveying the images represented to CRT or film. Due to the inherent characteristic of radiograph, the pathology features always exhibit in the form of small size image signal with low contrast and noisy staining. To investigate the detectivity of human vision on these will help to solve the problem in what condition just-noticeable differences can be detected, and then to choose proper x-ray tube voltage and current to make x-ray exposure. In this work, a software of improved 4-forced choice experiment is developed. This experiment is performed to test observer performance in more than 600 groups respectively. By ROC analyzing, an exact range of some image parameters is detected to satisfy the Rose model. Some results are obtained as follows: when observer can detect JND with 50% TPF, the minimum contrast is approximately 1%, while background intensity is 20% of the maximum intensity and the value of k in Rose model approximately varies from 2 to 3 as target area changing. The minimum contrast decreases when the background intensity is above 20%.
In this paper, we aim at a polychromatic physics model of dual-energy medical x-ray imaging and present a corresponding computation method, which includes two steps: first, bd(s, theta), i.e. the parameter used for expressing the component of Compton scatter, and bp(s, theta), i.e. the parameter used for expressing the component of Photoemission Effect, are decided by solving a nonlinear equation system; then a FBP ( Filtered Back Projection ) algorithm is used to reconstruct the decomposition images from the sinograms of bp(s, theta) and bp(s, theta). It is noticed that the first step is the most time-consuming, so it is very important to find out a high-speed and effective iteration computation method. In this paper, we propose a Newton iteration method with an effective estimation strategy of initial value for quickly solving the nonlinear equation system. A CT simulation experiment was implemented to validate the effectiveness of the whole procedure.