tfio.image.decode_dicom_image
Stay organized with collections
Save and categorize content based on your preferences.
Getting DICOM Image Data.
tfio.image.decode_dicom_image(
contents, color_dim=False, on_error='skip',
scale='preserve', dtype=tf.uint16, name=None
)
Used in the notebooks
This package has two operations which wrap DCMTK
functions.
decode_dicom_image
decodes the pixel data from DICOM files, and
decode_dicom_data
decodes tag information.
dicom_tags
contains useful DICOM tags such as dicom_tags.PatientsName
.
We borrow the same tag notation from the
pydicom
dicom package.
The detailed usage of DICOM is available in
tutorial.
If this package helped, please kindly cite the below:
@misc{marcelo_lerendegui_2019_3337331,
author = {Marcelo Lerendegui and Ouwen Huang},
title = {Tensorflow Dicom Decoder},
month = jul,
year = 2019,
doi = {10.5281/zenodo.3337331},
url = {<a href="https://doi.org/10.5281/zenodo.3337331">https://doi.org/10.5281/zenodo.3337331</a>}
}
Args |
contents
|
A Tensor of type string. 0-D. The byte string encoded DICOM file.
|
color_dim
|
An optional bool . Defaults to False . If True , a third
channel will be appended to all images forming a 3-D tensor.
A 1024 x 1024 grayscale image will be 1024 x 1024 x 1.
|
on_error
|
Defaults to skip . This attribute establishes the behavior in
case an error occurs on opening the image or if the output type cannot
accomodate all the possible input values. For example if the user sets
the output dtype to tf.uint8 , but a dicom image stores a tf.uint16
type. strict throws an error. skip returns a 1-D empty tensor.
lossy continues with the operation scaling the value via the scale
attribute.
|
scale
|
Defaults to preserve . This attribute establishes what to do with
the scale of the input values. auto will autoscale the input values,
if the output type is integer, auto will use the maximum output scale
for example a uint8 which stores values from [0, 255] can be linearly
stretched to fill a uint16 that is [0,65535]. If the output is float,
auto will scale to [0,1]. preserve keeps the values as they are, an
input value greater than the maximum possible output will be clipped.
|
dtype
|
An optional tf.DType from: tf.uint8 , tf.uint16 , tf.uint32 ,
tf.uint64 , tf.float16 , tf.float32 , tf.float64 . Defaults to
tf.uint16 .
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor of type dtype and the shape is determined by the DICOM file.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2022-02-15 UTC.
[null,null,["Last updated 2022-02-15 UTC."],[],[],null,["# tfio.image.decode_dicom_image\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/io/blob/v0.24.0/tensorflow_io/python/ops/dicom_ops.py#L25-L91) |\n\nGetting DICOM Image Data. \n\n tfio.image.decode_dicom_image(\n contents, color_dim=False, on_error='skip',\n scale='preserve', dtype=tf.uint16, name=None\n )\n\n### Used in the notebooks\n\n| Used in the tutorials |\n|-------------------------------------------------------------------------------------------|\n| - [Decode DICOM files for medical imaging](https://www.tensorflow.org/io/tutorials/dicom) |\n\nThis package has two operations which wrap `DCMTK` functions.\n`decode_dicom_image` decodes the pixel data from DICOM files, and\n`decode_dicom_data` decodes tag information.\n`dicom_tags` contains useful DICOM tags such as [`dicom_tags.PatientsName`](../../tfio/image/dicom_tags#PatientsName).\nWe borrow the same tag notation from the\n[`pydicom`](https://pydicom.github.io/) dicom package.\n\nThe detailed usage of DICOM is available in\n[tutorial](https://www.tensorflow.org/io/tutorials/dicom).\n\nIf this package helped, please kindly cite the below: \n\n @misc{marcelo_lerendegui_2019_3337331,\n author = {Marcelo Lerendegui and Ouwen Huang},\n title = {Tensorflow Dicom Decoder},\n month = jul,\n year = 2019,\n doi = {10.5281/zenodo.3337331},\n url = {\u003ca href=\"https://doi.org/10.5281/zenodo.3337331\"\u003ehttps://doi.org/10.5281/zenodo.3337331\u003c/a\u003e}\n }\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `contents` | A Tensor of type string. 0-D. The byte string encoded DICOM file. |\n| `color_dim` | An optional `bool`. Defaults to `False`. If `True`, a third channel will be appended to all images forming a 3-D tensor. A 1024 x 1024 grayscale image will be 1024 x 1024 x 1. |\n| `on_error` | Defaults to `skip`. This attribute establishes the behavior in case an error occurs on opening the image or if the output type cannot accomodate all the possible input values. For example if the user sets the output dtype to [`tf.uint8`](https://www.tensorflow.org/api_docs/python/tf#uint8), but a dicom image stores a [`tf.uint16`](https://www.tensorflow.org/api_docs/python/tf#uint16) type. `strict` throws an error. `skip` returns a 1-D empty tensor. `lossy` continues with the operation scaling the value via the `scale` attribute. |\n| `scale` | Defaults to `preserve`. This attribute establishes what to do with the scale of the input values. `auto` will autoscale the input values, if the output type is integer, `auto` will use the maximum output scale for example a `uint8` which stores values from \\[0, 255\\] can be linearly stretched to fill a `uint16` that is \\[0,65535\\]. If the output is float, `auto` will scale to \\[0,1\\]. `preserve` keeps the values as they are, an input value greater than the maximum possible output will be clipped. |\n| `dtype` | An optional [`tf.DType`](https://www.tensorflow.org/api_docs/python/tf/dtypes/DType) from: [`tf.uint8`](https://www.tensorflow.org/api_docs/python/tf#uint8), [`tf.uint16`](https://www.tensorflow.org/api_docs/python/tf#uint16), [`tf.uint32`](https://www.tensorflow.org/api_docs/python/tf#uint32), [`tf.uint64`](https://www.tensorflow.org/api_docs/python/tf#uint64), [`tf.float16`](https://www.tensorflow.org/api_docs/python/tf#float16), [`tf.float32`](https://www.tensorflow.org/api_docs/python/tf#float32), [`tf.float64`](https://www.tensorflow.org/api_docs/python/tf#float64). Defaults to [`tf.uint16`](https://www.tensorflow.org/api_docs/python/tf#uint16). |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `dtype` and the shape is determined by the DICOM file. ||\n\n\u003cbr /\u003e"]]