Research Focus
I feel joined with the UN sustainable development goals (SDGs), specifically goal 3 which claims to “ensure healthy lives and promote well-being for all at all ages“ with one focus on reproductive, maternal, newborn and child health.
In line with this, one major aspect of my research deals with the understanding of placental functions. The placenta tries to guarantee proper fetal development and is thus very important for the development of the adult phenotype of the offspring. It exhibits plasticity and can adopt when facing an adverse environment such as maternal under- and over-nutrition or exposure to drugs or environmental pollutants.
However, when the placental capacity for adaption is exceeded, the regular function of the placenta is disturbed and/or the placenta does not develop properly, then the foetus becomes affected, which subsequently can impact on the life-long health of the foetus. This concept is known as fetal programming of diseases.
Considering some of the major health problems of today including under-nutrition on one hand and increasing obesity rates on the other hand as well as the many environmental pollutants known today, I consider deciphering physiologic and pathophysiologic functions of the placenta as extremely relevant for our future health and thus this research area will remain an important topic of my future work.
Another focus of goal 3 is to achieve universal access to essential health care services.
Histopathological image analysis is required for diagnosis of malignant lesions. But even for experienced pathologists the diagnosis process is not trivial.
Diagnostic concordance between specialists is on average only 75%. Moreover, there is a lack of pathologists in many parts of the world. These limitations motivate the development of Computer-Aided Diagnosis (CAD) systems based on automated image analysis algorithms.
Being a second opinion system, CAD systems shall reduce the workload of specialists, improve the diagnosis efficiency, and contribute to cost reduction.
In addition, automated image analysis is a big data analysis tool that is of high interest for biomedical researchers.
I am interested in using and further developing automated image analysis in ongoing and future collaborative research projects with the ultimate aim to identify new biomarkers, better understand specific diseases and advance personalized medicine.