119 citations · 341 across the 8 of their papers we have counts for
8 papers
Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification
Amirreza Mahbod, Rupert Ecker, Ramona Woitek
Accurate classification of skin lesions from dermatoscopic images is essential for diagnosis and treatment of skin cancer. In this study, we investigate the utility of a dermatolog…
Community-developed checklists for publishing images and image analysis
Christopher Schmied, Michael Nelson, Sergiy Avilov +51
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. H…
Automatic Foot Ulcer Segmentation Using an Ensemble of Convolutional Neural Networks
Amirreza Mahbod, Gerald Schaefer, Rupert Ecker +1
Foot ulcer is a common complication of diabetes mellitus and, associated with substantial morbidity and mortality, remains a major risk factor for lower leg amputations. Extracting…
CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological Images
Amirreza Mahbod, Gerald Schaefer, Benjamin Bancher +4
Nuclei instance segmentation plays an important role in the analysis of Hematoxylin and Eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent t…
Pollen Grain Microscopic Image Classification Using an Ensemble of Fine-Tuned Deep Convolutional Neural Networks
Amirreza Mahbod, Gerald Schaefer, Rupert Ecker +1
Pollen grain micrograph classification has multiple applications in medicine and biology. Automatic pollen grain image classification can alleviate the problems of manual categoris…
The Effects of Skin Lesion Segmentation on the Performance of Dermatoscopic Image Classification
Amirreza Mahbod, Philipp Tschandl, Georg Langs +2
Malignant melanoma (MM) is one of the deadliest types of skin cancer. Analysing dermatoscopic images plays an important role in the early detection of MM and other pigmented skin l…