Literature DB >> 28859252

Open access database of raw ultrasonic signals acquired from malignant and benign breast lesions.

Hanna Piotrzkowska-Wróblewska1, Katarzyna Dobruch-Sobczak1,2, Michał Byra1, Andrzej Nowicki1.   

Abstract

PURPOSE: The aim of this paper is to provide access to a database consisting of the raw radio-frequency ultrasonic echoes acquired from malignant and benign breast lesions. The database is freely available for study and signal analysis. ACQUISITION AND VALIDATION
METHODS: The ultrasonic radio-frequency echoes were recorded from breast focal lesions of patients of the Institute of Oncology in Warsaw. The data were collected between 11/2013 and 10/2015. Patients were examined by a radiologist with 18 yr' experience in the ultrasonic examination of breast lesions. The set of data includes scans from 52 malignant and 48 benign breast lesions recorded in a group of 78 women. For each lesion, two individual orthogonal scans from the pathological region were acquired with the Ultrasonix SonixTouch Research ultrasound scanner using the L14-5/38 linear array transducer. All malignant lesions were histologically assessed by core needle biopsy. In the case of benign lesions, part of them was histologically assessed and another part was observed over a 2-year period. DATA FORMAT AND USAGE NOTES: The radio-frequency echoes were stored in Matlab file format. For each scan, the region of interest was provided to correctly indicate the lesion area. Moreover, for each lesion, the BI-RADS category and the lesion class were included. Two code examples of data manipulation are presented. The data can be downloaded via the Zenodo repository (https://doi.org/10.5281/zenodo.545928) or the website http://bluebox.ippt.gov.pl/~hpiotrzk. POTENTIAL APPLICATIONS: The database can be used to test quantitative ultrasound techniques and ultrasound image processing algorithms, or to develop computer-aided diagnosis systems.
© 2017 American Association of Physicists in Medicine.

Entities:  

Keywords:  breast lesions; dataset; ultrasonic signals; ultrasonography

Mesh:

Year:  2017        PMID: 28859252     DOI: 10.1002/mp.12538

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  8 in total

Review 1.  Methods for the segmentation and classification of breast ultrasound images: a review.

Authors:  Ademola E Ilesanmi; Utairat Chaumrattanakul; Stanislav S Makhanov
Journal:  J Ultrasound       Date:  2021-01-11

2.  Explaining a Deep Learning Based Breast Ultrasound Image Classifier with Saliency Maps.

Authors:  Michał Byra; Katarzyna Dobruch-Sobczak; Hanna Piotrzkowska-Wroblewska; Ziemowit Klimonda; Jerzy Litniewski
Journal:  J Ultrason       Date:  2022-04-27

Review 3.  Virtual clinical trials in medical imaging: a review.

Authors:  Ehsan Abadi; William P Segars; Benjamin M W Tsui; Paul E Kinahan; Nick Bottenus; Alejandro F Frangi; Andrew Maidment; Joseph Lo; Ehsan Samei
Journal:  J Med Imaging (Bellingham)       Date:  2020-04-11

4.  Internet-based digital video atlas of sonographic findings for clinical and educational purposes.

Authors:  Daniel Merkel; Christoph Schneider; Michael Ludwig
Journal:  J Ultrason       Date:  2020-03-31

5.  Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network.

Authors:  Michal Byra; Piotr Jarosik; Aleksandra Szubert; Michael Galperin; Haydee Ojeda-Fournier; Linda Olson; Mary O'Boyle; Christopher Comstock; Michael Andre
Journal:  Biomed Signal Process Control       Date:  2020-06-26       Impact factor: 3.880

6.  Breast Tumor Classification Using Intratumoral Quantitative Ultrasound Descriptors.

Authors:  Sabiq Muhtadi
Journal:  Comput Math Methods Med       Date:  2022-03-07       Impact factor: 2.238

7.  A quantization assisted U-Net study with ICA and deep features fusion for breast cancer identification using ultrasonic data.

Authors:  Talha Meraj; Wael Alosaimi; Bader Alouffi; Hafiz Tayyab Rauf; Swarn Avinash Kumar; Robertas Damaševičius; Hashem Alyami
Journal:  PeerJ Comput Sci       Date:  2021-12-16

8.  Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging.

Authors:  Yali Ouyang; Po-Hsiang Tsui; Shuicai Wu; Weiwei Wu; Zhuhuang Zhou
Journal:  Diagnostics (Basel)       Date:  2019-11-08
  8 in total

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