A review of career devoted to biophotonics-in memoriam to Ekaterina Borisova (1978-2021)

Regretfully, because of her sudden demise, Assoc. Prof. Ekaterina Borisova is no longer amongst us. COVID-19 pulled away a brilliant scientist during the peak of her scientific career (see Fig. 1). All authors would like to express deepest condolences and sincere support to her family, friends, relatives and colleagues! We, therefore, rightfully commemorate her dedicated and devoted contribution to biophotonics, her readiness to always support, help, motivate and inspire all her colleagues and collaborators

Mezencefalni oblik meningoencefalitis a u bolesnice s HL A-B51 beh cetovom bolešću: prikaz slučaja

This case report is a detailed description of the clinical, laboratory, imaging and therapeutic characteristics of the sixth patient with neuro-Behcet’s disease reported by Bulgarian authors. The diagnosis was made in accordance with the international diagnostic criteria for Behcet’s disease and was verified by skin biopsy. Therapeutic response was followed up by clinical and magnetic resonance imaging data for 6 months. Discussed are differences in the classical Behcet’s disease presentation and other neuro-Behcet’s disease cases found in Bulgaria. The current case supports the wide clinical heterogeneity of the disorder and the variety of therapeutic options.U ovom prikazu slučaja daje se iscrpan opis kliničkih, laboratorijskih, slikovno prikaznih i terapijskih značajka šestog bolesnika s neuro-Behcetovom bolešću o kojem izvješćuju bugarski autori. Dijagnoza je postavljena na osnovi međunarodnih dijagnostičkih kriterija za Behcetovu bolest i potvrđena biopsijom kože. Odgovor na terapiju pratio se kliničkim podacima i nalazima magnetske rezonancije kroz 6 mjeseci. Raspravlja se o razlikama u manifestiranju klasične Behcetove bolesti i drugim slučajevima neuro-Behcetove bolesti u Bugarskoj. Prikazani slučaj govori u prilog velike heterogenosti ove bolesti te o potrebi vrlo raznovrsnih terapijskih pristupa

Polarization-Based Digital Histology of Human Skin Biopsies Assisted by Deep Learning

Mueller polarimetry has proven to be a powerful optical technique to complement medical doctors in their conventional histology analysis. In this work, various degenerative and malignant human skin lesions were evaluated ex vivo using imaging Mueller polarimetry. The Mueller matrix images of thin sections of biopsies were recorded and the differential decomposition of Mueller matrices was applied pixel-wise to extract the polarization fingerprint of the specimens under study. To improve the classification accuracy, a deep learning model was created. The results indicate the sensitivity of polarimetry to different skin lesions and healthy skin zones and their differentiation, while using standard histological analysis as a ground truth. In particular, the deep learning model was found sufficiently accurate to detect and differentiate between all eight classes in the data set. Special attention was paid to the overfitting problem and the reduction of the loss function of the model. Our approach is an effort in establishing digital histology for clinical applications by complementing medical doctors in their diagnostic decisions