no code implementations • 12 Dec 2023 • Henrik Skibbe, Michal Byra, Akiya Watakabe, Tetsuo Yamamori, Marco Reisert
We introduce "PatchMorph," an new stochastic deep learning algorithm tailored for unsupervised 3D brain image registration.
1 code implementation • 8 Aug 2023 • Michal Byra, Charissa Poon, Tomomi Shimogori, Henrik Skibbe
We propose a novel image registration method based on implicit neural representations that addresses the challenging problem of registering a pair of brain images with similar anatomical structures, but where one image contains additional features or artifacts that are not present in the other image.
no code implementations • 8 Aug 2023 • Michal Byra, Muhammad Febrian Rachmadi, Henrik Skibbe
Moreover, we assess the ability of VLMs to evaluate shape features in breast mass ultrasound images.
1 code implementation • 13 Mar 2023 • Charissa Poon, Muhammad Febrian Rachmadi, Michal Byra, Matthias Schlachter, Binbin Xu, Tomomi Shimogori, Henrik Skibbe
We present the first automated pipeline to create an atlas of in situ hybridization gene expression in the adult marmoset brain in the same stereotaxic space.
no code implementations • 3 Nov 2022 • Michal Byra, Piotr Karwat, Ivan Ryzhankow, Piotr Komorowski, Ziemowit Klimonda, Lukasz Fura, Anna Pawlowska, Norbert Zolek, Jerzy Litniewski
Standard classification methods based on handcrafted morphological and texture features have achieved good performance in breast mass differentiation in ultrasound (US).
no code implementations • 11 Oct 2022 • Michal Byra, Ziemowit Klimonda, Piotr Jarosik
We develop neural networks that can estimate the HK distribution parameters based on the signal-to-noise ratio, skewness and kurtosis calculated using fractional-order moments.
no code implementations • 19 May 2022 • Piotr Jarosik, Michal Byra, Marcin Lewandowski, Ziemowit Klimonda
Attenuation coefficient (AC) is a fundamental measure of tissue acoustical properties, which can be used in medical diagnostics.
no code implementations • 7 Sep 2020 • Michal Byra, Grzegorz Styczynski, Cezary Szmigielski, Piotr Kalinowski, Lukasz Michalowski, Rafal Paluszkiewicz, Bogna Ziarkiewicz-Wroblewska, Krzysztof Zieniewicz, Andrzej Nowicki
In ultrasound (US) imaging, CNNs have been applied to object classification, image reconstruction and tissue characterization.
no code implementations • 27 Jan 2020 • Michal Byra, Piotr Jarosik, Katarzyna Dobruch-Sobczak, Ziemowit Klimonda, Hanna Piotrzkowska-Wroblewska, Jerzy Litniewski, Andrzej Nowicki
In comparison to commonly applied segmentation methods, which use US images, our approach is based on quantitative entropy parametric maps.
no code implementations • 5 Aug 2019 • Michal Byra, Mei Wu, Xiaodong Zhang, Hyungseok Jang, Ya-Jun Ma, Eric Y Chang, Sameer Shah, Jiang Du
Next, the T1, T1$\rho$, T2* relaxations, and ROI areas were determined for the manual and automatic segmentations, then compared. The models developed using ROIs provided by two radiologists achieved high Dice scores of 0. 860 and 0. 833, while the radiologists' manual segmentations achieved a Dice score of 0. 820.
no code implementations • 27 May 2019 • Michal Byra, Michael Andre
While benign breast masses tend to have a well-defined ellipsoidal contour, shape of malignant breast masses is commonly ill-defined and highly variable.
no code implementations • 6 Apr 2018 • Michal Byra, Tomasz Sznajder, Danijel Korzinek, Hanna Piotrzkowska-Wroblewska, Katarzyna Dobruch-Sobczak, Andrzej Nowicki, Krzysztof Marasek
We show that the augmentation of the training set with differently reconstructed B-mode images leads to a more robust and efficient classification.