no code implementations • 7 May 2024 • Nematollah Saeidi, Hossein Karshenas, Bijan Shoushtarian, Sepideh Hatamikia, Ramona Woitek, Amirreza Mahbod
Breast cancer is a significant global health concern, particularly for women.
no code implementations • 12 Sep 2023 • Amirreza Mahbod, Georg Dorffner, Isabella Ellinger, Ramona Woitek, Sepideh Hatamikia
With the advent of digital pathology and microscopic systems that can scan and save whole slide histological images automatically, there is a growing trend to use computerized methods to analyze acquired images.
no code implementations • 3 Sep 2023 • Sepideh Hatamikia, Geevarghese George, Florian Schwarzhans, Amirreza Mahbod, Ramona Woitek
For smoothing and erosion, VOIs yielded the highest number of robust features and the best prediction performance, while ellipse fitting and dilation lead to the lowest robustness and prediction performance for both breast cancer subtypes.
1 code implementation • 3 Aug 2023 • Amirreza Mahbod, Christine Polak, Katharina Feldmann, Rumsha Khan, Katharina Gelles, Georg Dorffner, Ramona Woitek, Sepideh Hatamikia, Isabella Ellinger
In this work, we release one of the biggest fully manually annotated datasets of nuclei in Hematoxylin and Eosin (H&E)-stained histological images, called NuInsSeg.
no code implementations • 15 Jun 2022 • Amirreza Mahbod, Rahim Entezari, Isabella Ellinger, Olga Saukh
We investigate the impact of weight pruning on the performance of both branches separately and on the final nuclei instance segmentation result.
no code implementations • 2 Jan 2022 • Chuanbo Wang, Amirreza Mahbod, Isabella Ellinger, Adrian Galdran, Sandeep Gopalakrishnan, Jeffrey Niezgoda, Zeyun Yu
Segmentation of wound boundaries in images is a key component of the care and diagnosis protocol since it is important to estimate the area of the wound and provide quantitative measurement for the treatment.
1 code implementation • 3 Sep 2021 • Amirreza Mahbod, Gerald Schaefer, Rupert Ecker, Isabella Ellinger
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.
1 code implementation • MICCAI Workshop COMPAY 2021 • Benjamin Bancher, Amirreza Mahbod, Isabella Ellinger, Rupert Ecker, Georg Dorffner
Recently, instance-aware segmentation methods such as Mask R-CNN have been proposed to enable unified instance detection and segmentation, even in overlapping cases.
1 code implementation • 2 Jan 2021 • Amirreza Mahbod, Gerald Schaefer, Benjamin Bancher, Christine Löw, Georg Dorffner, Rupert Ecker, Isabella Ellinger
Analysis of FS-derived H&E stained images can be more challenging as rapid preparation, staining, and scanning of FS sections may lead to deterioration in image quality.
no code implementations • 15 Nov 2020 • Amirreza Mahbod, Gerald Schaefer, Rupert Ecker, Isabella Ellinger
Our proposed method is shown to yield excellent classification performance, obtaining an accuracy of of 94. 48% and a weighted F1-score of 94. 54% on the ICPR 2020 Pollen Grain Classification Challenge training dataset based on five-fold cross-validation.
1 code implementation • 28 Aug 2020 • Amirreza Mahbod, Philipp Tschandl, Georg Langs, Rupert Ecker, Isabella Ellinger
In this study, we explicitly investigated the impact of using skin lesion segmentation masks on the performance of dermatoscopic image classification.
no code implementations • 25 Jun 2020 • Amirreza Mahbod, Gerald Schaefer, Chunliang Wang, Rupert Ecker, Georg Dorffner, Isabella Ellinger
Our results show that using very small images (of size 64x64 pixels) degrades the classification performance, while images of size 128x128 pixels and above support good performance with larger image sizes leading to slightly improved classification.
no code implementations • 27 Feb 2017 • Amirreza Mahbod, Gerald Schaefer, Chunliang Wang, Rupert Ecker, Isabella Ellinger
In this work, we propose a fully automatic computerised method for skin lesion classification which employs optimised deep features from a number of well-established CNNs and from different abstraction levels.