This paper presents a comparison of different implementations of 3D anisotropic diffusion speckle noise reduction
technique on ultrasound images. In this project we are developing a novel volumetric calcification assessment metric for
the placenta, and providing a software tool for this purpose. The tool can also automatically segment and visualize (in
3D) ultrasound data. One of the first steps when developing such a tool is to find a fast and efficient way to eliminate
Previous works on this topic by Duan, Q.  and Sun, Q.  have proven that the 3D noise reducing anisotropic
diffusion (3D SRAD) method shows exceptional performance in enhancing ultrasound images for object segmentation.
Therefore we have implemented this method in our software application and performed a comparative study on the
different variants in terms of performance and computation time. To increase processing speed it was necessary to utilize the full potential of current state of the art Graphics Processing Units (GPUs).
Our 3D datasets are represented in a spherical volume format. With the aim of 2D slice visualization and segmentation, a "scan conversion" or "slice-reconstruction" step is needed, which includes coordinate transformation from spherical to Cartesian, re-sampling of the volume and interpolation.
Combining the noise filtering and slice reconstruction in one process on the GPU, we can achieve close to real-time operation on high quality data sets without the need for down-sampling or reducing image quality. For the GPU programming OpenCL language was used. Therefore the presented solution is fully portable.
This study reports an incidental finding from a larger work. It examines the relationship between spatial
resolution and nodule detection for chest radiographs. Twelve examining radiologists with the
American Board of Radiology read thirty chest radiographs in two conditions - full (1500 × 1500
pixel) resolution, and 300 × 300 pixel resolution linearly interpolated to 1500 × 1500 pixels. All
images were surrounded by a 10-pixel sharp grey border to aid in focussing the observer's eye when
viewing the comparatively unsharp interpolated images. Fifteen of the images contained a single
simulated pulmonary nodule. Observers were asked to rate their confidence that a nodule was present
on each radiograph on a scale of 1 (least confidence, certain no lesion is present) to 6 (most confidence,
certain a lesion was present). All other abnormalities were to be ignored. No windowing, levelling or
magnification of the images was permitted and viewing distance was constrained to approximately
70cm. Images were displayed on a 3 megapixel greyscale monitor. Receiver operating characteristic
(ROC) analysis was applied to the results of the readings using the Dorfman-Berbaum-Metz multiplereader,
multiple-case method. No statistically significant differences were found with either readers
and cases treated as random or with cases treated as fixed. Low spatial frequency information appears
to be sufficient for the detection of chest lesion of the type used in this study.
This study aimed to measure the sound levels in Irish x-ray departments. The study then established whether these levels
of noise have an impact on radiologists performance
Noise levels were recorded 10 times within each of 14 environments in 4 hospitals, 11 of which were locations where
radiologic images are judged. Thirty chest images were then presented to 26 senior radiologists, who were asked to
detect up to three nodular lesions within 30 posteroanterior chest x-ray images in the absence and presence of noise at
amplitude demonstrated in the clinical environment.
The results demonstrated that noise amplitudes rarely exceeded that encountered with normal conversation with the
maximum mean value for an image-viewing environment being 56.1 dB. This level of noise had no impact on the ability
of radiologists to identify chest lesions with figure of merits of 0.68, 0.69, and 0.68 with noise and 0.65, 0.68, and 0.67
without noise for chest radiologists, non-chest radiologists, and all radiologists, respectively. the difference in their
performance using the DBM MRMC method was significantly better with noise than in the absence of noise at the 90%
confidence interval (p=0.077). Further studies are required to establish whether other aspects of diagnosis are impaired
such as recall and attention and the effects of more unexpected noise on performance.
In order to prevent specular reflections, many monitor faceplates have features such as tiny dimples on their surface to
diffuse ambient light incident on the monitor, however, this "anti-glare" surface may also diffuse the image itself. The
purpose of the study was to determine whether the surface characteristics of monitor faceplates influence the detection of
pulmonary nodules under low and high ambient lighting conditions.
Methods and Materials
Separate observer performance studies were conducted at each of two light levels (<1 lux and >250 lux). Twelve
examining radiologists with the American Board of Radiology participated in the darker condition and eleven in the
brighter condition. All observers read on both smooth "glare" and dimpled "anti-glare" faceplates in a single lighting
condition. A counterbalanced methodology was utilized to minimise memory effects. In each reading, observers were
presented with thirty chest images in random order, of which half contained a single simulated pulmonary nodule. They
were asked to give their confidence that each image did or did not contain a nodule and to mark the suspicious location.
ROC analysis was applied to resultant data.
No statistically significant differences were seen in the trapezoidal area under the ROC curve (AUC), sensitivity,
specificity or average time per case at either light level for chest specialists or radiologists from other specialities.
The characteristics of the faceplate surfaces do not appear to affect detection of pulmonary nodules. Further work into
other image types is being conducted.
Dynamic cueing is an effective way of stimulating perception of regions of interest within radiological images. This
study explores the impact of a novel teaching tool using dynamic cueing for lesion detection on plain chest radiographs.
Materials and methods
Observer performance studies were carried out where 36 novices examined 30 chest images in random order. Half of
these contained between one and three simulated pulmonary nodules. Three groups were investigated: A (control: no
teaching tool), B (retested immediately after undergoing the teaching tool) and C (retested a week after undergoing the
teaching tool). The teaching tool involved dynamically displaying the same images with and without lesions. Results
were compared using Receiver Operating Characteristics (ROC), sensitivity and specificity analyses.
The second reading showed significantly greater area under the ROC curve (Az value) (p<0.0001) and higher sensitivity
value (p=0.004) compared to the first reading for Group B. No differences between readings were demonstrated for
groups A or C. When the magnitudes of the above changes were compared between Group B and the other two groups,
greater changes in Az value for Group B were noted (B vs. A:p=0.0003, B vs. C:p=0.0005). For sensitivity, when Group
B was compared to Group A, the magnitude of the change was significantly greater (p=0.0029) whereas when Group B
was compared to Group C, the magnitude change demonstrated a level approaching significance (p=0.0768).
The novel teaching tool improves identification of pulmonary nodular lesions on chest radiographs in the short term.
Current ultrasound assessment of placental calcification relies on Grannum grading. The aim of this study was to assess
if this method is reproducible by measuring inter- and intra-observer variation in grading placental images, under strictly
controlled viewing conditions. Thirty placental images were acquired and digitally saved. Five experienced sonographers
independently graded the images on two separate occasions. In order to eliminate any technological factors which could
affect data reliability and consistency all observers reviewed images at the same time. To optimise viewing conditions
ambient lighting was maintained between 25-40 lux, with monitors calibrated to the GSDF standard to ensure consistent
brightness and contrast. Kappa (κ) analysis of the grades assigned was used to measure inter- and intra-observer
reliability. Intra-observer agreement had a moderate mean κ-value of 0.55, with individual comparisons ranging from
0.30 to 0.86. Two images saved from the same patient, during the same scan, were each graded as I, II and III by the
same observer. A mean κ-value of 0.30 (range from 0.13 to 0.55) indicated fair inter-observer agreement over the two
occasions and only one image was graded consistently the same by all five observers. The study findings confirmed the
lack of reproducibility associated with Grannum grading of the placenta despite optimal viewing conditions and
highlight the need for new methods of assessing placental health in order to improve neonatal outcomes. Alternative
methods for quantifying placental calcification such as a software based technique and 3D ultrasound assessment need to
The unavoidable distance between the cervical spine and the image receptor presents measurable levels of geometric
unsharpness, which hinders arthritic scoring. The current work explores the impact on the visualisation of important
arthritic indicators by increasing the distance between the X-ray source and image detector (SID) from the commonly
employed 150cm. Lateral cervical spine images were acquired of an osteoarthritic human cadaver using a DR imaging
system. All exposures were taken at 65kVp using automatic exposure control and various SID distances from 150 to
210cm. Four experienced clinicians assessed the images by means of visual grading analysis, using objective criteria
based on normal anatomic features and arthritic indicators. A statistically significant improvement in image quality was
observed with images acquired at 210cm compared with those acquired at 150cm and 180cm (p<0.05), with values of
56.0 (SE=1.105), 50.85 (SE=1.415) and 65.35 (SE=0.737) respectively. All images with a SID of 210cm scored higher
for visually sharp reproduction of the spinous processes, facet joints, intervertebral disc spaces and trabecular bone
pattern compared with both 180cm and 150cm. Results indicate that total image quality and visualisation of specific
anatomical features is improved in cervical spine radiographs when traditionally employed SID distances are increased.
In obstetrics, antenatal ultrasound assessment of placental morphology comprises an important part of the estimation of
fetal health. Ultrasound analysis of the placenta may reveal abnormalities such as placental calcification and infarcts.
Current methods of quantification of these abnormalities are subjective and involve a grading system of Grannum stages
I-III. The aim of this project is to develop a software tool that quantifies semi-automatically placental ultrasound images
and facilitates the assessment of placental morphology. We have developed a 2D ultrasound imaging software tool that
allows the obstetrician or sonographer to define the placental region of interest. A secondary reference map is created for
use in our quantification algorithm. Using a slider technique the user can easily define an upper threshold based on high
intensity for calcification classification and a lower threshold to define infarction regions based on low intensity within
the defined region of interest. The percentage of the placental area that is calcified and also the percentage of infarction is
calculated and this is the basis of our new metric. Ultrasound images of abnormal and normal placentas have been
acquired to aid our software development. A full clinical prospective evaluation is currently being performed and we are
currently applying this technology to the three-dimensional ultrasound domain. We have developed a novel software-based
technique for calculating the extent of placental calcification and infarction, providing a new metric in this field.
Our new metric may provide a more accurate measurement of placental calcification and infarction than current
Visualisation of anatomical or pathological image data is highly dependent on the eye's ability to discriminate between
image brightnesses and this is best achieved when these data are presented to the viewer at luminance levels to which the
eye is adapted. Current ambient light recommendations are often linked to overall monitor luminance but this relies on
specific regions of interest matching overall monitor brightness.
The current work investigates the luminances of specific regions of interest within three image-types: postero-anterior
(PA) chest; PA wrist; computerised tomography (CT) of the head. Luminance levels were measured within the hilar
region and peripheral lung distal radius and supra-ventricular grey matter. For each image type average monitor
luminances were calculated with a calibrated photometer at ambient light levels of 0, 100 and 400 lux. Thirty samples of
each image-type were employed, resulting in a total of over 6,000 measurements.
Results demonstrate that average monitor luminances varied from clinically-significant values by up to a factor of 4, 2
and 6 for chest, wrist and CT head images respectively. Values for the thoracic hilum and wrist were higher and for the
peripheral lung and CT brain lower than overall monitor levels. The ambient light level had no impact on the results.
The results demonstrate that clinically important radiological information for common radiological examinations is not
being presented to the viewer in a way that facilitates optimised visual adaptation and subsequent interpretation. The
importance of image-processing algorithms focussing on clinically-significant anatomical regions instead of radiographic
projections is highlighted.
Detection of low-contrast details is highly dependent on the adaptation state of the eye. It is important therefore that the
average luminance of the observer's field of view (FOV) matches those of softcopy radiological images. This study
establishes the percentage of FOV filled by workstations at various viewing distances.
Five observers stood at viewing distances of 20, 30 and 50cm from a homogenous white surface and were instructed to
continuously focus on a fixed object at a height appropriate level. A dark indicator was held at this object and then
moved steadily until the observer could no longer perceive it in his/her peripheral vision. This was performed at 0°, 90°,
180° and 270° clockwise from the median sagittal plane. Distances were recorded, radii calculated and observer and
mean FOV areas established. These values were then compared with areas of typical high and low specification
Individual and mean FOVs were 7660, 15463 and 30075cm<sup>2</sup> at viewing distances of 20, 30 and 50cm respectively. High
and low specification monitors with respective areas of 1576.25 and 921.25cm<sup>2</sup> contributed between 5 to 21% and 3 to
12% respectively to the total FOV depending on observer distance. Limited inter-observer variances were noted.
Radiology workstations typically comprise between only 3 and 21% of the observer's FOV. This demonstrates the
importance of measuring ambient light levels and surface reflection coefficients in order to maximise adaptation and
observer's perception of low contrast detail and minimise eye strain.
Clinical radiological judgments are increasingly being made on softcopy LCD monitors. These monitors are found throughout the hospital environment in radiological reading rooms, outpatient clinics and wards. This means that ambient lighting where clinical judgments from images are made can vary widely. Inappropriate ambient lighting has several deleterious effects: monitor reflections reduce contrast; veiling glare adds brightness; dynamic range and detectability of low contrast objects is limited. Radiological images displayed on LCDs are more sensitive to the impact of inappropriate ambient lighting and with these devices problems described above are often more evident.
The current work aims to provide data on optimum ambient lighting, based on lesions within chest images. The data provided may be used for the establishment of workable ambient lighting standards. Ambient lighting at 30cms from the monitor was set at 480 Lux (office lighting) 100 Lux (WHO recommendations), 40 Lux and <10 Lux. All monitors were calibrated to DICOM part 14 GSDF.
Sixty radiologists were presented with 30 chest images, 15 images having simulated nodular lesions of varying subtlety and size. Lesions were positioned in accordance with typical clinical presentation and were validated radiologically. Each image was presented for 30 seconds and viewers were asked to identify and score any visualized lesion from 1-4 to indicate confidence level of detection. At the end of the session, sensitivity and specificity were calculated. Analysis of the data suggests that visualization of chest lesions is affected by inappropriate lighting with chest radiologists demonstrating greater ambient lighting dependency. JAFROC analyses are currently being performed.
We report on the development of a novel software tool for the simulation of chest lesions. This software tool was developed for use in our study to attain optimal ambient lighting conditions for chest radiology. This study involved 61 consultant radiologists from the American Board of Radiology. Because of its success, we intend to use the same tool for future studies. The software has two main functions: the simulation of lesions and retrieval of information for ROC (Receiver Operating Characteristic) and JAFROC (Jack-Knife Free Response ROC) analysis. The simulation layer operates by randomly selecting an image from a bank of reportedly normal chest x-rays. A random location is then generated for each lesion, which is checked against a reference lung-map. If the location is within the lung fields, as derived from the lung-map, a lesion is superimposed. Lesions are also randomly selected from a bank of manually created chest lesion images. A blending algorithm determines which are the best intensity levels for the lesion to sit naturally within the chest x-ray. The same software was used to run a study for all 61 radiologists. A sequence of images is displayed in random order. Half of these images had simulated lesions, ranging from subtle to obvious, and half of the images were normal. The operator then selects locations where he/she thinks lesions exist and grades the lesion accordingly. We have found that this software was very effective in this study and intend to use the same principles for future studies.