Digital methods, tools and algorithms are gaining in importance for the analysis of digitized manuscript collections
in the arts and humanities. One example is the BMBF-funded research project “eCodicology” which
aims to design, evaluate and optimize algorithms for the automatic identification of macro- and micro-structural
layout features of medieval manuscripts. The main goal of this research project is to provide better insights into
high-dimensional datasets of medieval manuscripts for humanities scholars. The heterogeneous nature and size
of the humanities data and the need to create a database of automatically extracted reproducible features for
better statistical and visual analysis are the main challenges in designing a workflow for the arts and humanities.
This paper presents a concept of a workflow for the automatic tagging of medieval manuscripts. As a starting
point, the workflow uses medieval manuscripts digitized within the scope of the project Virtual Scriptorium St.
Matthias". Firstly, these digitized manuscripts are ingested into a data repository. Secondly, specific algorithms
are adapted or designed for the identification of macro- and micro-structural layout elements like page size,
writing space, number of lines etc. And lastly, a statistical analysis and scientific evaluation of the manuscripts
groups are performed. The workflow is designed generically to process large amounts of data automatically with
any desired algorithm for feature extraction. As a result, a database of objectified and reproducible features is
created which helps to analyze and visualize hidden relationships of around 170,000 pages. The workflow shows
the potential of automatic image analysis by enabling the processing of a single page in less than a minute.
Furthermore, the accuracy tests of the workflow on a small set of manuscripts with respect to features like page
size and text areas show that automatic and manual analysis are comparable. The usage of a computer cluster
will allow the highly performant processing of large amounts of data. The software framework itself will be
integrated as a service into the DARIAH infrastructure to make it adaptable for wider range of communities.
The paper presents a new ultrasonic attenuation imaging method
which might be used as a new imaging modality, targeted at breast
cancer diagnostics. Two approaches based on ultrasonic imaging are
combined together, namely the estimation of ultrasound attenuation
coefficients from pulse-echo B-mode imaging data and an ultrasound
computer tomography imaging technique. A recently published method
for estimation of the ultrasound attenuation coefficient using the
log--spectrum analysis is applied to radiofrequency signals
acquired by an ultrasound computer tomography system to estimate
images of the attenuation coefficients.
The examined volume (e.g. female breast) is enclosed by several
thousand ultrasound transducers. Radiofrequency signals from all
transducers using all sending positions are recorded. Compared to
the known ultrasound attenuation tomography methods, not only the
directly transmitted signal, but also the reflected and scattered
signals are processed here, i.e. substantially more information is
The method is presented in its initial stage. The applied algorithm
is derived using simplifying assumptions which will be relaxed in
further research. However, even at this stage the resulting attenuation image is of higher quality than the standard attenuation
imaging methods applied to the same data set.
Ultrasound computer tomography is an imaging method capable of
producing volume images with high spatial resolution. The imaged
object is enclosed by a cylindrical array of transducers. While
one transducer emits a spherical wavefront (pulse), all other
transducers are recording the radiofrequency (RF) a-scans
simultaneously. Then another transducer acts as the emitter and so
In this paper we describe the image reconstruction method and an
enhanced algorithm for the a-scan preprocessing. The image
reconstruction is based on a 'full aperture sum-and-delay'
algorithm evaluating the reflected and scattered signals in the
a-scans. The a-scans are modelled as the tissue response of the
imaged object convoluted with the shape of the ultrasound pulse,
which is determined by the transfer function of the transducers
and the excitation. Spiking deconvolution and blind deconvolution
with different parameters are used to build inverse filters of the
ultrasound pulse. Applying the inverse filters to the a-scans
results in sharper signals which are used for image
reconstruction. Smallest scatterers of 0.1 mm size corresponding
to one fifth of the used ultrasound wavelength are visible in the
reconstructed images. Compared to conventional b-scans the
resulting images show an approximately tenfold better resolution.
Ultrasound computer tomography is an imaging method capable of producing volume images with both high spatial and temporal resolution. The promising results of a 2D experimental setup of an ultrasound computer tomography system with at least 0.25 mm resolution encouraged us to build a new 3D demonstration system. It consists of three parts: a tank containing the sensor system, a data acquisition hardware and a computer workstation for image reconstruction and visualization. For the sensor system we developed and manufactured our own low-cost transducer array emitting or receiving ultrasound signals in three dimensions. To optimize the transducer geometry in respect to aperture angle and pressure amplitude the pressure field was simulated using the ultrasound simulation program Field II. Each transducer arrays system carries 8 emitting and 32 receiving elements with integrated amplifier and address electronics. 192 A-scans can be recorded in parallel by the data acquisition hardware. 48 multiplexing steps are needed to store all A-scans of the 1536 receiving transducers. After recording the data is transmitted to the computer workstation.
Ultrasound computer-tomography (USCT) is a novel ultrasound imaging method capable of producing volume images with both high spatial and temporal resolution. Several thousand ultrasound transducers are arranged in a cylindrical array around a tank containing the object to be examined coupled by water. Every single transducer is small enough to emit an almost spherical sound-wave. While one transducer is transmitting, all others receive simultaneously. Our experimental setup, using only a few transducers simulating a ring-shaped
geometry, showed even nylon threads (0.1 mm) with an image quality superior to clinical in-use ultrasound scanners. In order to build a complete circular array several thousand transducers, with
cylindrical sound field characteristics, are needed. Since such transducer arrays are hardly available and expensive, we developed inexpensive transducer arrays consisting of 8 elements. Each array is based on a plate of lead titanate zirconate ceramics (PZT) sawn into 8 elements of 0.3 mm width, 3.8 mm height and 0.5 mm pitch. Each element has a mean frequency of 3.8 MHz and can be triggered
separately. The main challenge was the development of production steps with reproducible results. Our transducer arrays show only small variances in the sound field characteristics which are strongly required for ultrasound tomography.
In breast cancer diagnosis, ultrasound examination provides useful additional diagnostic information. Moreover ultrasound does not harm biological tissue and can be applied frequently. But conventional ultrasound imaging methods lack both high spatial and temporal resolution. Usually, the scanner is operated manually and the tissue is deformed while getting as close as possible to the regions of interest. Therefore, image contents and image quality depend strongly on the operator. Exact measurement of tissue structures, like tumor size, is not possible. Instead of a manually controlled linear transducer array, we use ultrasound computer tomography (USCT) to image a volume directly. A few thousand ultrasound transducers are arranged in a cylindrical array around a tank containing the object to be examined coupled by water. Every single transducer is small enough to emit an almost spherical sound wave. While one transducer is transmitting, all others receive simultaneously. Afterwards a different transducer emits the next pulse. For volume reconstruction every transmitted, scattered and reflected signal is used. This new method allows reproducible image sequences with enhanced spatial and temporal resolution. For the benefit of more reconstructed 3D images per second, spatial resolution may be reduced offline. First tests with our prototype in a ring-shaped geometry have even showed nylon threads (0.4 mm) and an image quality superior to clinical ultrasound scanners.
The development of computer assisted diagnosis systems for image-patterns is still in the early stages compared to the powerful image and object recognition capabilities of the human eye and visual cortex. Rules have to be defined and features have to be found manually in digital images to come to an automatic classification. The extraction of discriminating features is especially in medical applications a very time consuming process. The quality of the defined features influences directly the classification success. Artificial neural networks are in principle able to solve complex recognition and classification tasks, but their computational expenses restrict their use to small images. A new improved image object classification scheme consists of neural networks as feature extractors and common statistical discrimination algorithms. Applied to the recognition of different types of tumor nuclei images this system is able to find differences which are barely discernible by human eyes.
This work describes the three-dimensional reconstruction of clustered microcalcifications based on only two digitized mammograms. First, the mammograms are examined separately to detect suspicious areas automatically. A further investigation separates microcalcifications from other structures. Based on an optimized region matching and on a specially adapted inverse discrete radon-transformation the corresponding volume is estimated from two projections and visualized by a continuously rotating object. But do two projections of a cluster carry enough information to reconstruct its three- dimensional arrangement sufficiently? We use Shannon's definition of information to estimate a lower bound of preserved information, described as the ratio of average information contained in the projections and average information contained in the volume, for simplified scenarios. Assuming two orthogonal projections of a cubic volume containing k binary representations of microcalcification positions the average information in the projections is determined by the combinatorial quantity of admissible arrangements and the size n3 of the volume. The combinatorial quantity of legal three-dimensional arrangements of microcalcification positions describes the average information carried by the volume. We showed that the amount of preserved information in the projections is more than 95% if k equals n/2 positions are found in both projections; it will exceed 98% if k equals n/4 positions are set.
X-ray mammography is one of the most significant diagnosis methods in early detection of breast cancer. Usually two X- ray images from different angles are taken from each mamma to make even overlapping structures visible. X-ray mammography has a very high spatial resolution and can show microcalcifications of 50 - 200 micron in size. Clusters of microcalcifications are one of the most important and often the only indicator for malignant tumors. These calcifications are in some cases extremely difficult to detect. Computer assisted diagnosis of digitized mammograms may improve detection and interpretation of microcalcifications and cause more reliable diagnostic findings. We build a low-cost mammography workstation to detect and classify clusters of microcalcifications and tissue densities automatically. New in this approach is the estimation of the 3D formation of segmented microcalcifications and its visualization which will put additional diagnostic information at the radiologists disposal. The real problem using only two or three projections for reconstruction is the big loss of volume information. Therefore the arrangement of a cluster is estimated using only the positions of segmented microcalcifications. The arrangement of microcalcifications is visualized to the physician by rotating.