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Pawłowska A., Ćwierz-Pieńkowska A.♦, Domalik A.♦, Jaguś D., Kasprzak P.♦, Matkowski R.♦, Fura , Nowicki A., Żołek N.S., Curated benchmark dataset for ultrasound based breast lesion analysis,
Scientific Data, ISSN: 2052-4463, DOI: 10.1038/s41597-024-02984-z, Vol.11, No.148, pp.1-13, 2024Streszczenie: A new detailed dataset of breast ultrasound scans (BrEaST) containing images of benign and malignant lesions as well as normal tissue examples, is presented. The dataset consists of 256 breast scans collected from 256 patients. Each scan was manually annotated and labeled by a radiologist experienced in breast ultrasound examination. In particular, each tumor was identified in the image using a freehand annotation and labeled according to BIRADS features and lexicon. The histopathological classification of the tumor was also provided for patients who underwent a biopsy.
The BrEaST dataset is the first breast ultrasound dataset containing patient-level labels, image-level annotations, and tumor-level labels with all cases confirmed by follow-up care or core needle biopsy result. To enable research into breast disease detection, tumor segmentation and classification, the BrEaST dataset is made publicly available with the CC-BY 4.0 license. Afiliacje autorów:
Pawłowska A. | - | IPPT PAN | Ćwierz-Pieńkowska A. | - | inna afiliacja | Domalik A. | - | inna afiliacja | Jaguś D. | - | IPPT PAN | Kasprzak P. | - | inna afiliacja | Matkowski R. | - | inna afiliacja | Fura | - | IPPT PAN | Nowicki A. | - | IPPT PAN | Żołek N.S. | - | IPPT PAN |
| | 140p. |
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Pawłowska A., Żołek N., Leśniak-Plewińska B.♦, Dobruch-Sobczak K., Klimonda Z., Piotrzkowska-Wróblewska H., Litniewski J., Preliminary assessment of the effectiveness of neoadjuvant chemotherapy in breast cancer with the use of ultrasound image quality indexes,
Biomedical Signal Processing and Control, ISSN: 1746-8094, DOI: 10.1016/j.bspc.2022.104393, Vol.80, No.104393, pp.1-9, 2023Streszczenie: Objective: Neoadjuvant chemotherapy (NAC) in breast cancer requires non-invasive methods of monitoring its effects after each dose of drug therapy. The aim is to isolate responding and non-responding tumors prior to surgery in order to increase patient safety and select the optimal medical follow-up. Methods: A new method of monitoring NAC therapy has been proposed. The method is based on image quality indexes (IQI) calculated from ultrasound data obtained from breast tumors and surrounding tissue. Four different tissue regions from the preliminary set of 38 tumors and three data pre-processing techniques are considered. Postoperative histopathology results were used as a benchmark in evaluating the effectiveness of the IQI classification. Results: Out of ten parameters considered, the best results were obtained for the Gray Relational Coefficient. Responding and non-responding tumors were predicted after the first dose of NAC with an area under the receiver operating characteristics curve of 0.88 and 0.75, respectively. When considering subsequent doses of NAC, other IQI parameters also proved usefulness in evaluating NAC therapy. Conclusions: The image quality parameters derived from the ultrasound data are well suited for assessing the effects of NAC therapy, in particular on breast tumors.
Słowa kluczowe: Quantitative ultrasound; Image quality; Neoadjuvant chemotherapy; Breast cancer; Treatment response Afiliacje autorów:
Pawłowska A. | - | IPPT PAN | Żołek N. | - | IPPT PAN | Leśniak-Plewińska B. | - | inna afiliacja | Dobruch-Sobczak K. | - | IPPT PAN | Klimonda Z. | - | IPPT PAN | Piotrzkowska-Wróblewska H. | - | IPPT PAN | Litniewski J. | - | IPPT PAN |
| | 140p. |
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Pawłowska A., Karwat P., Żołek N.S., Letter to the Editor. Re: "[Dataset of breast ultrasound images" by W. Al-Dhabyani, M. Gomaa, H. Khaled & A. Fahmy, Data in Brief, 2020, 28, 104863]",
Data in Brief, ISSN: 2352-3409, DOI: 10.1016/j.dib.2023.109247, Vol.48C, pp.109247--, 2023Streszczenie: In an interesting article previously published in Data in Brief [Dataset of breast ultrasound images" by W. Al-Dhabyani, M. Gomaa, H. Khaled & A. Fahmy, Data in Brief, 2020, 28, 104863], the authors presented a dataset of breast ultrasound images containing lesions. As of April 22, 2023, this study has garnered significant attention from researchers, as evident by its 298 citations in Scopus data. This is unsurprising considering that the study presents one of the few publicly available datasets on breast ultrasound images, as well as binary masks highlighting the lesions. When implementing various aspects of explainable AI, we verify the correctness of the input data at every stage, especially when using various data sources. In an attempt to use this dataset for research, we did some exploration and identified some inconsistencies that could have a significant impact on the results of the studies utilizing them. As the role of tumor detection is indisputable we feel obliged to point attention to some aspects that need to be kept in mind while using this database in order to receive reliable and good quality results. Afiliacje autorów:
Pawłowska A. | - | IPPT PAN | Karwat P. | - | IPPT PAN | Żołek N.S. | - | IPPT PAN |
| | 40p. |