A. Przelaskowski

发表

Feature Extraction Optimized For Prostate Lesion Classification

K. Sklinda, Piotr Sobecki, Dominika Zycka-Malesa, 2017, ICBBT '17.

Sparse signal compaction for lossless audio coding: integrated approach

A. Przelaskowski, 2015 .

CT diagnosis of early stroke : the initial approach to the new CAD tool based on multiscale estimation of ischemia

K. Sklinda, J. Walecki, A. Przelaskowski, 2009 .

ACUTE ISCHEMIC STROKE : ENHANCED DISPLAY OF HYPODENSE CHANGES

K. Sklinda, J. Walecki, A. Przelaskowski, 2006 .

ACUTE ISCHEMIC STROKE: ENHANCED DISPLAY OF HYPODENSE CHANGES IN CT EXAMS

K. Sklinda, J. Walecki, A. Przelaskowski, 2006 .

Improving the predictiveness of ICU medical scales by the method of pairwise comparisons

Waldemar W. Koczkodaj, Tamar Kakiashvili, K. Rutkowski, 2011, FedCSIS.

Using group theory in pairwise comparisons: a brief critique

W. W. Koczkodaj, V. Marek, L. Mikhailov, 2019 .

Spicule descriptors designed in complex wavelet domain to recognize breast cancer symptoms

A. Przelaskowski, R. Józwiak, Magdalena Jasionowska, 2014 .

ENHANCEMENT OF ACCURACY IN MAMMOGRAMS INTERPRETATION USING ONTOLOGY-DRIVEN EDITOR FOR LESIONS DESCRIPTION AND CAD TOOL - PRELIMINARY RESULTS

A. Przelaskowski, T. Podsiadly-Marczykowska, Anna Wróblewska, 2007 .

Three Stage Method Assisting Endobronchial Tumor Mass Recognition in Bronchoscopy Images

A. Przelaskowski, R. Józwiak, R. Jóźwiak, 2010 .

NUMERICAL EQUIVALENT OF ACCURACY AS A MEASURE OF MEDICAL IMAGE QUALITY

A. Przelaskowski, 2003 .

Computer-aided interpretation of medical images: mammography case study

Artur Przelaskowski, Anna Wróblewska, Pawel Bargiel, 2007 .

Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies

Artur Przelaskowski, Weronika Hryniewska, Przemyslaw Bombinski, 2020, Pattern Recognition.

Recovery of CT stroke hypodensity - An adaptive variational approach

Artur Przelaskowski, A. Przelaskowski, 2015, Comput. Medical Imaging Graph..

Adaptive Sparse Recovery of Medical Images with Variational Approach – Preliminary Study for CT Stroke

Artur Przelaskowski, A. Przelaskowski, 2014 .

Perception Enhancement of Bronchoscopic Video

M. Duplaga, A. Rutczyńska, A. Przelaskowski, 2010 .

Development of Diagnostic Stroke Ontology - Preliminary Results

Artur Przelaskowski, Teresa Podsiadly-Marczykowska, Bogdan Ciszek, 2014 .

Effect of domain knowledge encoding in CNN model architecture—a prostate cancer study using mpMRI images

K. Sklinda, Piotr Sobecki, A. Przelaskowski, 2021, PeerJ.

On the use of group theory to generalize elements of pairwise comparisons matrix: A cautionary note

W. W. Koczkodaj, W. Pedrycz, V. Marek, 2019, Int. J. Approx. Reason..

Improving the predictability of ICU illness severity scales

K. Rutkowski, A. Przelaskowski, T. Kakiashvili, 2011, 2011 Federated Conference on Computer Science and Information Systems (FedCSIS).

A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis

Kenny H. Cha, Krzysztof J. Geras, Md Belayat Hossain, 2023, JAMA network open.

Effective integer-to-integer transforms for JPEG2000 coder

Artur Przelaskowski, A. Przelaskowski, 2001, SPIE Optics + Photonics.

Angular Resolution Study of Vectors Representing Subtle Spiculated Structures in Mammograms

Artur Przelaskowski, Magdalena Jasionowska, A. Przelaskowski, 2014 .

A Two-Step Method for Detection of Architectural Distortions in Mammograms

Artur Przelaskowski, Magdalena Jasionowska, Aleksandra Rutczyńska, 2010 .

Neuroimaging of Cerebral Venous Thrombosis (CVT) – Old Dilemma and the New Diagnostic Methods

K. Sklinda, B. Mruk, J. Walecki, 2015, Polish journal of radiology.

Improved mammogram interpretation with an ontology-driven editor and mammoviewer - preliminary results

A. Przelaskowski, T. Podsiadly-Marczykowska, Anna Wróblewska, 2008 .

Multiscale extraction of hypodensity in hyperacute stroke.

K. Sklinda, J. Walecki, A. Przelaskowski, 2007, Medical Science Monitor.

Improved early stroke detection: Wavelet-based perception enhancement of computerized tomography exams

Artur Przelaskowski, Katarzyna Sklinda, Pawel Bargiel, 2007, Comput. Biol. Medicine.

ACUTE STROKE DETECTION IN UNENHANCED CT EXAMS: PERCEPTION ENHANCEMENT BY MULTI-SCALE APPROACH * (DËUGO TYTUËU NIE POWINNA PRZEKRACZA 2 WIERSZY)

J. Walecki, A. Przelaskowski, Katarzyna Szerewicz, 2006 .

Improving diagnostic value of CT examinations in hyperacute ischemic stroke.

K. Sklinda, J. Walecki, A. Przelaskowski, 2010, Acta neurochirurgica. Supplement.

Stroke Tissue Pattern Recognition Based on CT Texture Analysis

Grzegorz Ostrek, Artur Przelaskowski, Artur Nowakowski, 2015, CORES.

MRI imaging texture features in prostate lesions classification

Artur Przelaskowski, Ihor Mykhalevych, Piotr Sobecki, 2017 .

Conceptual improvements in computer-aided diagnosis of acute stroke

Grzegorz Ostrek, Artur Przelaskowski, A. Przelaskowski, 2011 .

Assessment of Uterine Contractile Activity during a Pregnancy Based on a Nonlinear Analysis of the Uterine Electromyographic Signal

Artur Przelaskowski, D. Radomski, Antony Grzanka, 2008, Information Technologies in Biomedicine.