duke_ultrasound

Note: This dataset has been updated since the last stable release. The new versions and config marked with are only available in the tfds-nightly package.

• Description:

DukeUltrasound is an ultrasound dataset collected at Duke University with a Verasonics c52v probe. It contains delay-and-sum (DAS) beamformed data as well as data post-processed with Siemens Dynamic TCE for speckle reduction, contrast enhancement and improvement in conspicuity of anatomical structures. These data were collected with support from the National Institute of Biomedical Imaging and Bioengineering under Grant R01-EB026574 and National Institutes of Health under Grant 5T32GM007171-44. A usage example is available here.

• Homepage: https://github.com/ouwen/mimicknet

• Source code: tfds.datasets.duke_ultrasound.Builder

• Versions:

  • 1.0.0: Initial release.
  • 1.0.1: Fixes parsing of boolean field harmonic.
  • 2.0.0 (default) : Fix timestamp_id from %Y%m%d%H%M%S to posix timestamp.

• Download size: 12.78 GiB

• Dataset size: 13.79 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'A'	1,362
'B'	1,194
'MARK'	420
'test'	438
'train'	2,556
'validation'	278

• Feature structure:

FeaturesDict({
    'das': FeaturesDict({
        'dB': Tensor(shape=(None,), dtype=float32),
        'imag': Tensor(shape=(None,), dtype=float32),
        'real': Tensor(shape=(None,), dtype=float32),
    }),
    'dtce': Tensor(shape=(None,), dtype=float32),
    'f0_hz': float32,
    'final_angle': float32,
    'final_radius': float32,
    'focus_cm': float32,
    'harmonic': bool,
    'height': uint32,
    'initial_angle': float32,
    'initial_radius': float32,
    'probe': string,
    'scanner': string,
    'target': string,
    'timestamp_id': uint32,
    'voltage': float32,
    'width': uint32,
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
das	FeaturesDict
das/dB	Tensor	(None,)	float32
das/imag	Tensor	(None,)	float32
das/real	Tensor	(None,)	float32
dtce	Tensor	(None,)	float32
f0_hz	Tensor		float32
final_angle	Tensor		float32
final_radius	Tensor		float32
focus_cm	Tensor		float32
harmonic	Tensor		bool
height	Tensor		uint32
initial_angle	Tensor		float32
initial_radius	Tensor		float32
probe	Tensor		string
scanner	Tensor		string
target	Tensor		string
timestamp_id	Tensor		uint32
voltage	Tensor		float32
width	Tensor		uint32

• Supervised keys (See as_supervised doc): ('das/dB', 'dtce')

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@article{DBLP:journals/corr/abs-1908-05782,
  author    = {Ouwen Huang and
               Will Long and
               Nick Bottenus and
               Gregg E. Trahey and
               Sina Farsiu and
               Mark L. Palmeri},
  title     = {MimickNet, Matching Clinical Post-Processing Under Realistic Black-Box
               Constraints},
  journal   = {CoRR},
  volume    = {abs/1908.05782},
  year      = {2019},
  url       = {http://arxiv.org/abs/1908.05782},
  archivePrefix = {arXiv},
  eprint    = {1908.05782},
  timestamp = {Mon, 19 Aug 2019 13:21:03 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1908-05782},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}