#Imagej software nature paper full

#Imagej software nature paper full

However, this technique involves the manipulation of huge images (of the order of 10 billions of pixels for a full-size slide at magnification 40x with a single focus level) for which the approach taken by most standard software, loading and decompressing the full image into RAM, is impossible (a single slice of a full-size slide needs of the order of 30 GiB of RAM). An accurate, non-pixelated determination of the perimeters of the cell nuclei is needed for morphometry and statistics.

For instance, the state of the chromatin inside the nucleus and the cell morphology, better seen at high magnification, are essential to help the clinician distinguish tumorous and non-tumorous cells. The benefit of the high magnification for both diagnosis and automated image analysis is clear. As an example, Figure 1 shows two portions of a slide at different magnifications, 10x and 40x. They allow much better visualization and analysis than lower magnification images. Modern slide scanners produce high magnification microscopy images of excellent quality, for instance at the so-called “40x” magnification. This growing use of virtual microscopy is accompanied by the development of integrated image analysis systems offering both virtual slide scanning and automatic image analysis, which makes integration into the daily practice of pathologists easier. Databases of clinical cases will include more and more digitized tissue images. A growing number of works report the pertinence of such images for diagnosis and classification of diseases, e.g. Quantitative histology is a promising new field, involving computer-based morphometry or statistical analysis of tissues. mathematicians and clinicians who do not work at the same location. They have also a great potential for research, especially in the context of multidisciplinary projects involving e.g. In more and more hospitals, virtual slides are even attached to the patient’s file. Virtual microscopy has become routinely used over the last few years for the transmission of pathology images (the so-called virtual slides), for both telepathology and teaching. The virtual slide(s) for this article can be found here: They open promising perspectives both to the clinician who wants to study a single slide and to the research team or data centre who do image analysis of many slides on a computer cluster. They have excellent performance in terms of execution speed and RAM requirements. They are cross-platform, independent of proprietary libraries and very modular, allowing them to be used in other open source projects.

Our open source software enables dealing with huge images with standard software on average computers. A statistical study of the cells in a tissue sample from an oligodendroglioma was performed on an average laptop computer to demonstrate the efficiency of the tools. We test the performance of these tools on several digital slides and compare them, when applicable, to standard software. The LargeTIFFTools achieve similar functionality for huge TIFF images which do not fit into RAM. They can be driven through ImageJ plugins. The NDPITools provide a way to transform microscopy images initially in the loosely supported NDPI format into one or several standard TIFF files, and to create mosaics (division of huge images into small ones, with or without overlap) in various TIFF and JPEG formats. We have developed several cross-platform open source software tools to overcome these limitations. Therefore, most common open source tools such as ImageJ fail at treating them, and the others require expensive hardware while still being prohibitively slow.

However, such virtual slides build up a technical challenge since the images occupy often several gigabytes and cannot be fully opened in a computer’s memory. Digital pathology images are increasingly used both for diagnosis and research, because slide scanners are nowadays broadly available and because the quantitative study of these images yields new insights in systems biology.