Scientific methods and patented technology.

Concentration and Motility Analysis

QualiSperm uses proprietary semen analysis algorithms based on fundamentally new technologies rendering reproductive analysis at all levels of concentration. Our Trajectory algorithm and Image Correlation Analysis Method, combined with advanced Digital Sperm Washing, delivers fast and accurate results.

Image Recognition

Using a larger field, QualiSperm is able to determine more sperms per unit area than any other CASA software. Its advanced image recognition algorithm captures up to 1000 sperms per image within only 4 seconds and further increases accuracy by scanning as many individual fields as are needed to reach a statistically relevant number.

Digital Sperm Washing

Our unique Digital Sperm Washing (DSW) algorithm significantly improves discrimination of non sperm objects within the captured images. This technology obliterates time consuming manual post processing and delivers precise results measuring concentration and motility.

Trajectory Analysis

In addition to very precise concentration results Qualisperm automatically renders adequate percentages for any given motility class within the same Analysis process. Tracking each sperms velocity averaged path (VAP) QualiSperm delivers precise trajectory analysis assessing the overall sperm velocity as well as fractions of sperms within the four WHO defined speed classes.

Image Correlation Analysis

Our own Image Correlation Analysis (IMA) method combined with the mentioned trajectory analysis delivers outstanding results at any concentration since combining the two methods has a unique complementary advantage; While trajectory analysis is very accurate when sperm concentration is low our image correlation method delivers excellent results at high concentrations. Together these two methods guarantee constant high quality results.



The sperm morphology module of QualiSperm is primarily based on mathematical morphology segmentation techniques. A dynamic local threshold operation transforms the grayscale microscope image into a binary matrix.

Several morphological shape-based filters are applied to identify various, specific sperm parts: head, acrosome, mid-piece and tail. The identified (segmented) sperm parts are then quantified in terms of purely geometric parameters such as length, width, area, angles, symmetry, perimeter and roughness.

Sperms are classified against the WHO and Kruger sperm normality criteria. For instance, a head shape is classified as tapered if the ratio between head length and head width is higher than its corresponding normality interval.


2020 – Chicken seminal fluid lacks CD9- and CD44-bearing
extracellular vesicles

Alvarez-Rodriguez M, Ntzouni M, Wright D, et al.
Reprod Dom Anim. 2020; 55: 293–300

2019 – Assessment of Oligo-Chitosan Biocompatibility toward Human Spermatozoa
Schimpf U, Nachmann G, Trombotto S, Houska P, Yan H, Björndahl L, Crouzier T
ACS Applied Materials & Interfaces 2019; 11:50, 46572-46584

2019 – A splice donor variant in CCDC189 is associated with asthenospermia in Nordic Red dairy cattle
Iso-Touru T, Wurmser C, Venhoranta H. et al
BMC Genomics 2019; 20:286

2019 – Diagnostics of DNA fragmentation in human spermatozoa: are sperm chromatin structure analysis and sperm chromatin
dispersion tests (SCD‐HaloSpermG2®) comparable?

Liffner S, Pehrson I, García‐Calvo L, Nedstrand E, Zalavary S, Hammar M, Rodriguez-Martinez H, Álvarez‐Rodríguez M.
Andrologia 2019; 51: e13316

2019 –  Evaluation of a portable device for assessment of motility in
stallion semen

Buss T, Aurich J, Aurich C.
Reprod Dom Anim. 2019; 54: 514–519

2018 –  Hyaluronan improves neither the long-term storage nor the cryosurvival of liquid-stored CD44-bearing AI boar spermatozoa
Alvarez-Rodriguez M, Vicente Carrillo A, Rodriguez-Martinez H.
J. Reprod. Dev. 2018; 64: 351–360

2017 – Conserved gene expression in sperm reservoirs between birds and mammals in response to mating
Atikuzzaman M, Alvarez-Rodriguez M, Vicente Carrillo A, Johnsson M, Wright D, Rodriguez-Martinez H.
BMC Genomics 2017; 18: 98

2017 – The CatSper channel modulates boar sperm motility during capacitation
Vicente-Carrillo A, Álvarez-Rodríguez M, Rodríguez-Martínez H.
Reproductive Biology 2017; 17: 69–78

2016 – Membrane stress during thawing elicits re-distribution of Aquaporin 7 but not of Aquaporin 9 in boar spermatozoa
Vicente-Carrillo A, Ekwall H, Álvarez-Rodríguez M, Rodríguez-Martínez H.
Reproduction in Domestic Animals 2016; 51: 665-679.

2016 – The mu (μ) and delta (δ) opioid receptors modulate boar sperm motility
Vicente-Carrillo A, Álvarez-Rodríguez M, Rodríguez-Martínez H.
Molecular Reproduction and Development 2016; 83: 724-734.

2015 – Boar spermotozoa successfully predict mitochondrial modes of toxicity: implications for drug toxicity testing and the 3R principles
Vicente-Carrillo A, Edebert I, Cotgreave H, Rigler R, Loitto V, Magnusson K E, Rodriguez-Martinez H.
Toxicology in Vitro 2015; 29: 582-591.

2013 – Semen evaluation techniques and their relationship with fertility
Rodriguez-Martinez H.
Animal Reproduction 2013; 10:3 148-159.

2011 – Boar spermatozoa peak compared to the remaining spermatozoa of the sperm-rich fraction
Siqueira A, Wallgren M, Hossain M, et al. Theriogenology 75:1175-1184.

2009 – Assessment of motility of ejaculated stallion spermatozoa using a novel computer-assisted motility analyzer (Qualisperm™)
Tejerina F, Morrell J, Petterson J, Dalin A-M & H Rodriguez-Martinez.
Animal Reprod 6: 380-385.

2009 – Colloidal centrifugation of stallion semen (during storage)
Morrell J, Johannisson A, Strutz H, et al. J Equine Vet Sci 29: 24-32.

2008 – Liquid-stored boar spermatozoa computerized instrument Assesement
Tejerina F, Buranaamnuay K, Saravia F, et al. Theriogenology 69: 1129-1138.

2008 – Influence of seminal plasma on the kinematics of boar spermatozoa during freezing
Rodriguez-Martinez H, Saravia F, Wallgren M, et al. Theriogenology 70: 1242-1250.

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