SLU-logoAssociate Professor at the Swedish University of Agricultural Sciences gives her verdict on the new Draminski iScan cattle ultrasound scanner...


Staff working in the barn of our university dairy herd has recently started using iScan for pregnancy diagnoses. They are licensed AI technicians and regularly perform all inseminations in the 240 cows plus recruitment heifers. Without previous experience of gynaecological ultrasound, they managed well at their very first attempts to identify the uterus and diagnose if a cow was pregnant or not.

After only one supervised training session together with an experienced veterinarian, they were competent enough to continue the training on their own. In their testimony, they say: iScan provides a clear image with high resolution. It is very easy to operate the scanner, e.g. to change the depth, save images, zoom in and out etc.

As a veterinarian with several years’ work experience in bovine reproduction including the use of transrectal ultrasonography, I regard iScan as a user-friendly, portable scanner with extremely high image quality. Compared to the previous portable model from Draminski (AnimalProfi L), iScan is notably lighter. Besides the weight reduction, there are numerous improvements made: There are less buttons and more logically structured functions under the menu button. It is possible to save not only frozen images but also cine loops. Moreover, it has been made possible to save images including calipers and measurement results. This detail facilitates record keeping for the herd’s sexual health control program, as well as for saving data in clinical research projects.


The monitor is smaller than in the previous model, which is compensated by the very high resolution of the 9 MHz probe; the image quality is greatly improved and it is possible to visualize really small details like the smallest antral follicles in the ovary and internal organs in early embryos. The casing of the scanner is “streamlined” and easy to clean. The batteries are attached in a new, smart manner with no cables and sockets needed, again making it easier to handle and clean. The scanner is ready to use as it is packed in the case, there is no time wasted on connecting the different parts.


A smart and functional shade is included in the kit which facilitates the work during bright or sunny days. In our work in bovine gynaecology in tropical countries, we could not manage without the shade. Occasionally, this also applies to scannings in Sweden, e.g. when examining beef cattle under outdoor conditions. Overall, we are very content with the iScan.

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" 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