A related problem is the storage of microscopic images. The National
Institute of Health (NIH) in America issued a call for proposals on this problem
in April 2009. Recent advances in technology have enabled researchers to
digitize pathological whole-slides at high magnifications (e.g. at 40).
Resulting colour microscopic images are large in size (e.g. 100K by 100K).
Therefore, finding efficient ways of compressing such images is necessary for
efficient transmission, storage and evaluation.
Currently, standard image compression methods such as JPEG or JPEG2000 are used.
However they do not take full advantage of the specific nature of microscopic
images. For example, IHC and H&E images contain textures that are “impulsive” in
nature, as shown in Figure-1 and their colour content depends on the staining
process. Therefore, compression methods suitably tailored for these images
should be developed. In this WP, we will address both the colour and the texture
aspects of the image compression problem.
Figure 1: IHC-stained microscopic image example
Recently, OSU and BILKENT developed a histogram-based colour transformation
method for microscopic images, that takes the image specific colour-content into
account and can be integrated with standard image compression methods like JPEG.
The conducted tests showed that, when applied to microscopic images, the
proposed method yields a mean compression ratio gain of about 20% for a given
PSNR value, compared to standard JPEG. Further compression with the JPEG and
JPEG-2000 will be carried out in this WP.
Image compression schemes for impulsively textured microscopic images will be
developed. We developed adaptive wavelet transform methods for isolated points
in 3D data [26,27]. It should be pointed out that all of the partners have
experience in wavelet analysis. We will develop an Adaptive Wavelet Transform (AWT)
[28,29] method for impulsively textured microscopic images. The method will take
advantage of the correlation between isolated impulsive pixels as in [26,27] and
this will lead to more efficient data compression results compared to the
ordinary wavelet transforms. We plan to encode the AWT coefficients using an
embedded zero tree. In this respect, Dr. Rajpoot’s expertise in adaptive
wavelets and zero-tree based methods for compression of images [30,31,32] will
be utilized for developing efficient histology image storage algorithms.
Storage and Representation
coding methods for microscopic images.
4.1: Image coding tests for modified colour transform methods.
4.2: Development of a modified adaptive wavelet transform taking
advantage of “impulsive” textured nature of FL and H&E images.
4.3: Image coding tests with JPEG, JPEG2000 and the proposed wavelet
17) Report on
the current methods of microscopic image compression.
18) Report on
the performance of modified colour-transform approach.
19) Image coding algorithms using adaptive wavelet transform and modified
20) Final report on the scientific work carried out in WP4 during the
-OSU: Dr. Metin N. Gurcan, Olcay Sertel
Prof. A. Enis Cetin, Alexander Suhre
-WARWICK: Dr. Nasir Rajpoot, Researcher 1, Researcher 2
Dr. Paulette Herlin, Researcher 5