Detection and volume estimation of artificial hematomas in the subcutaneous fatty tissue: comparison of different MR sequences at 3.0 T
Kathrin Ogris 0 1 2 3 4 5 6
Andreas Petrovic 0 1 2 3 4 5 6
Sylvia Scheicher 0 1 2 3 4 5 6
Hanna Sprenger 0 1 2 3 4 5 6
Martin Urschler 0 1 2 3 4 5 6
Eva Maria Hassler 0 1 2 3 4 5 6
Kathrin Yen 0 1 2 3 4 5 6
Eva Scheurer 0 1 2 3 4 5 6
0 Ludwig Boltzmann Institute for Clinical-Forensic Imaging , Graz , Austria
1 Institute of Forensic Medicine, Medical University of Graz , Universitaetsplatz 4/II, A-8010 Graz , Austria
2 Institute of Forensic Medicine, Health Department Basel, University Basel , Basel , Switzerland
3 Institute of Forensic and Traffic Medicine, University of Heidelberg , Heidelberg , Germany
4 Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz , Graz , Austria
5 Institute for Computer Graphics and Vision, Graz University of Technology , Graz , Austria
6 Institute for Biomedical Engineering, Graz University of Technology , Graz , Austria
In legal medicine, reliable localization and analysis of hematomas in subcutaneous fatty tissue is required for forensic reconstruction. Due to the absence of ionizing radiation, magnetic resonance imaging (MRI) is particularly suited to examining living persons with forensically relevant injuries. However, there is limited experience regarding MRI signal properties of hemorrhage in soft tissue. The aim of this study was to evaluate MR sequences with respect to their ability to show high contrast between hematomas and subcutaneous fatty tissue as well as to reliably determine the volume of artificial hematomas. Porcine tissue models were prepared by injecting blood into the subcutaneous fatty tissue to create
Imaging techniques like computed tomography (CT) and
magnetic resonance imaging (MRI) are well established in
many clinical applications, and various qualitative findings
and quantitative measurements derived from imaging data
are used to aid radiologists and clinicians in the diagnosis
and follow-up of different diseases. MRI and CT play a major
role in tumor diagnosis and staging e.g. in lung cancer [1–3],
breast tumors [4–6], prostate tumors [7–10], and brain tumors
[11–15], as well as in the follow-up of tumor progression [16,
17], often requiring volume measurements of tumor
structures. Another specific parameter is the volume measurement
of liquids in the assessment of hemorrhages. Further, volume
determination has proven especially useful for measurement
of liquid volumes in the assessment of hemorrhages , and
in the diagnosis and prognosis of cerebral bleedings . In
the case of cerebral hemorrhage, determination of both initial
hematoma volume and volume change, is essential as both
factors are independent predictors of treatment outcome and
mortality [20, 21]. Hence, CT and MRI protocols are well
established for the determination of these critical factors [19,
22–24]. In contrast, only limited knowledge exists on the
detection, volume estimation and investigation of hemorrhage in
soft tissue using MRI , as such lesions have less
Differently to clinical applications, in forensic medicine
information on blunt force injuries, especially hematomas in
the subcutaneous fatty tissue, are highly relevant .
Analysis of hematomas is required for forensic reconstruction
and verification of a specific course of events, especially in
cases involving child maltreatment or interpersonal violence.
To date, the gold standard for the detection of subcutaneous
hematomas due to blunt force is a detailed examination of the
entire body surface including photo documentation of any
visible lesions . Nevertheless, subcutaneous hematomas
are not necessarily visible externally, since visibility depends
on many factors, such as time since impact, pigmentation of
the skin or the amount of blood in the hemorrhage. In order to
obtain additional information regarding blunt force associated
with soft tissue injuries, the use of imaging methods, such as
CT and MRI has been proven to be beneficial .
Due to superior contrast achievable in soft tissue and
absence of ionizing radiation, MRI holds advantages over CT,
particularly if used in clinical forensic cases involving victims
of interpersonal violence. Although nowadays a growing
interest using MRI in forensic medicine is recognized, to date
there is only limited experience regarding the detection and
assessment of forensically relevant soft tissue injuries
Therefore, the aim of this study was the experimental
determination of the detection limits of subcutaneous blood
volumes in a porcine tissue model using 3.0 T MRI. Four MR
sequences were evaluated regarding their potential for precise
estimation of the blood volume of hemorrhages.
Materials & methods
Porcine tissue model preparation
into the subcutaneous fatty tissue of the pork belly to create
A total of 40 hematomas were injected into ten pork bellies
using four different blood volumes (0.1, 0.3, 0.6 and 1.0 mL).
The placement of the hematomas with the four different
volumes was performed randomly across the pork bellies. During
porcine tissue model preparation care was taken to only
introduce hematomas into the subcutaneous fatty tissue layer
(Fig. 1). Nevertheless, localization of hematomas in the
muscular tissue could not be completely prevented.
MR images of pork bellies preheated to approximately 37 °C
were acquired at 3.0 T (TimTrio, Siemens Healthcare,
Erlangen, Germany) using a combination of a spine and small
flex coil. The protocol consisted of the following four MR
sequences: T1 weighted (T1w) Fast Low Angle Shot
(FLASH), T1w Turbo Inversion Recovery (TIR), Proton
Density weighted (PDw) Turbo Spin Echo (TSE) with fat
saturation (FS), and T1w and T2w TSE sequence (see
Table 1). The sequences were chosen in order to maximize
contrast between hematomas and surrounding tissues.
Four blinded observers (3 forensic pathologists, 1 radiologist)
conducted manual segmentation of the 160 hematoma scans
(ten porcine tissue models, each with four hematomas and
four corresponding MR sequences) using the ITK-SNAP
 software (www.itksnap.org) by selecting all voxels
corresponding to the hematoma on each slice of the scan.
For image analysis the window level was fixed at
FullWidth Half-Maximum for each series and kept the same for
all observers. Figure 2 shows an example of a segmented scan.
Hematoma volumes were automatically calculated by the
ITK-SNAP software. For assessment of intra-observer
variability, segmentation was repeated after one week for 50%
of the hematomas (randomly selected).
Ten pork bellies from the butcher were prepared by injecting
freshly drawn venous blood from a healthy human volunteer
Table 1 Sequence parameters
used for the acquisition of MR
MR Magnetic Resonance, TE Echo Time, TR Repetition Time, TI Inversion Time, FLASH Fast Low Angle Shot,
TIR T1 weighted Turbo Inversion Recovery, PDw TSE FS Proton Density weighted Turbo Spin Echo with fat
saturation, T1wT2w TSE T1 and T2 weighted TSE sequence
Frequency cross tabulations were calculated to assess the
segmentability of all hematomas, all sequences, and volumes.
Hematomas were considered segmentable with a calculated
volume larger than 0. An additional forensic pathologist
decided whether the hematomas were only located in the
subcutaneous fatty tissue or also in the muscular tissue. The location
of the artificial lesions was considered in statistical analysis.
Accuracy and precision of volume measurements were
assessed both quantitatively using summary statistics and
graphically using boxplots of the estimated volumes (median,
25th and 75th percentiles, whiskers to demonstrate the lowest/
highest point within 1.5 × interquartile range [IQR], data
beyond these limits were considered outliers) for each rater,
sequence and hematoma size. In all diagrams the estimated
volume was plotted against the ground truth volume (injected
volume). Analysis was performed twice, initially for all
hematomas independent of their location and thereafter for
hematomas located in the subcutaneous fatty tissue only. Boxplots
Fig. 2 MR (Magnetic Resonance) image of a porcine tissue model
acquired with the T1T2w TSE (T1 and T2 weighted Turbo Spin Echo)
sequence. Colors represent the areas of the four artificial hematomas
identified during manual segmentation using ITK-SNAP software
show the pooled and averaged results of the forensic
pathologists, the radiologist, and finally for all observers.
Intra-observer reliability was determined by Bland-Altman
analysis , in which the mean value of two ratings was
plotted against their difference. Bias and the Limits of
Agreement (LoA) were calculated. For the assessment of
inter-observer reliability the same analysis was conducted
using the differences of the first rating of two distinct
observers. For intra- and inter-observer reliability analysis only
data from hematomas located in the subcutaneous fatty tissue
were taken into account, as the study and the protocol were
designed to focus on this issue.
A major requirement for a valid statistical analysis is the
homoscedasticity of the differences, i.e. the variance is
independent from actual hematoma size. Therefore, the correlation
(Kendall’s τ) between mean and absolute value of the
differences (V vs. |V1 − V2|) was calculated, to assess if there was a
systematic relationship. In case of heteroscedasticity either a
log-transform was applied, or the difference was normalized
by the mean (V1−V2 ). Calculation of Kendall’s τ showed that
there was significant heteroscedasticity in the differences, i.e.
the variance of the differences was dependent on the size of
the hematoma. In such cases a suitable transformation of the
data was sought. Of all the proposed transformations, a
physically motivated transformation model taking the partial
volume effect into account removed this heteroscedasticity most
effectively. Therefore, this transformation was considered to
be the best choice for further analysis and physically
motivated normalization was performed: Assuming a hematoma of
spherical form with radius ρ and “oversegmenting” a
relativelyffiffitffihffiffiin layer δ, the resulting error is proportional to ρ2δ, or
3 Vp2 ffi(ffiOffiffiffinline Resource 1). Hence, the difference was divided
again. Bias and LoA (and their corresponding confidence
intervals) were computed for the transformed data according to
Bland et al. . Subsequently, those pparffiffiaffiffimffieters were
backtransformed by multiplication with 3 V 2 to yield curved
limits and bias for the original data. For the assessment of
intra- and inter-observer variability the data were also
transformed prior to the computation of bias and LoA.
Subsequently, those values were back transformed and
Visual comparison of the four sequences showed good
positive or negative contrast between hematomas and the
subcutaneous fatty tissue. Hematomas were hyper intense in the
PDw TSE FS sequence (Fig. 3c), while in the other sequences
(FLASH, TIR, T1T2w TSE) they displayed as hypo intense
(Fig. 3a–d). During visual control it was found that 432 out of
the 640 segmentations were completely located in the
subcutaneous fatty tissue, the remaining 208 were at least partially
located in the muscular layers (illustrated by white rectangles
in Fig. 3).
(1.0 mL). Details regarding segmentability of all hematomas
are given in Table 2.
When hematomas located only in subcutaneous fatty tissue
were separately assessed, 428 out of 432 (99.1%) were
segmentable (Table 3), indicating an improved segmentability
for all used MR sequences (98.1% to 100%) compared to the
segmentation rate when all hematomas were considered.
TIR and PDw TSE FS sequences allowed segmentation of
all hematomas in the subcutaneous fatty tissue. Segmentation
rates related to injected blood volumes into fatty tissue ranged
between 96.4% for 0.3 mL and 100% for 0.1, 0.6, and 1.0 mL.
Accuracy and precision
The boxplots comparing volume estimation with ground truth
(Fig. 4) show that in general the medians of the determined
volumes were overestimated compared to the injected
volume, independent of the observers, sequences and locations.
In comparison to the analysis of all hematomas, those located
in subcutaneous fatty tissue showed less outliers and a reduced
IQR. This could be particularly well observed in the T1T2w
TSE sequence. Comparison of the medians of the estimated
volumes of the hematomas located in the subcutaneous fatty
tissue showed that these volumes were closest to the ground
truth (see Table 4, bold numbers).
Intra- and inter-observer reliability
In total, 640 hematomas were assessed using the ITK-SNAP
software. 611 out of 640 (95.5%) hematomas were
segmentable, with a segmentation rate ranging from 88.8%
to 100% depending on the used MR sequence. In contrast to
the other sequences, in the TIR sequence all hematomas could
be successfully segmented. The segmentation rate concerning
injected volumes ranged from 93.8% (0.3 mL) to 96.9%
Comparison of non-transformed and transformed data using
Bland-Altman analysis showed that the LoA tended to be too
broad for small hematoma volumes and too narrow for large
volumes. This deficiency was effectively removed by
applying the physically motivated transformation taking the partial
volume effect into account, which yielded curved limits for a
better description of the data (Fig. 5).
Fig. 3 MR (Magnetic
Resonance) images of a porcine
tissue model using four different
MR sequences: a FLASH, b TIR,
c PDw TSE FS, d T1T2w TSE.
The white rectangles highlight a
hematoma where the blood was
partly injected into the muscular
layer. (FLASH, Fast Low Angle
Shot; TIR, T1 weighted Turbo
Inversion Recovery; PDw TSE
FS, Proton Density weighted
Turbo Spin Echo with fat
saturation; T1wT2w TSE, T1 and
T2 weighted TSE sequence)
Table 2 Number of segmented
hematomas in relation to the total
number of artificially created
hematomas, separately for
different injected blood volumes
and MR sequences
MR Magnetic Resonance, FLASH Fast Low Angle Shot, TIR T1 weighted Turbo Inversion Recovery, PDw TSE
FS Proton Density weighted Turbo Spin Echo with fat saturation, T1wT2w TSE T1 and T2 weighted TSE
Figure 6 represents summarized results of intra-observer
reliability of estimations of hematoma volumes. On average
the slope of the bias curve was negative, i.e. the second
volume segmentation tended to be larger than the first. There was
substantial variation yielding LoA from −0.15 to 0.10 mL for
0.1 mL hematomas and from −0.70 to 0.45 mL for 1.0 mL.
With the TIR sequence, a slight positive bias was observed in
contrast to the other sequences. Additionally, the TIR
sequences showed lower LoA compared to the other sequences
(Online Resource 2).
The results for the assessment of inter-observer reliability
are presented in Fig. 7. The median LoA ranged from −0.21 to
0.11 mL for 0.1 mL hematomas and −0.96 to 0.49 mL for
1.0 mL. There was a small negative bias in all sequences, with
TIR and T1T2w TSE showing the lowest LoA (Online
Resource 3). Figure 7 depicts that the agreement between
the forensic pathologists is generally better than between
forensic pathologists and the radiologist.
Blunt force injuries, such as hematomas, are a matter of
special interest in forensic medicine. Although hematomas do not
usually have any therapeutic consequence, their presence can
have relevant implications for forensic reconstruction and
verification of a specific course of events.
In order to assess the detection limit of blood volumes in
subcutaneous tissue, artificial hematomas were
experimentally evaluated using different MR sequences in a porcine tissue
model. Firstly, the segmentability of the four studied MR
sequences was evaluated, followed by examination of accuracy
and precision of the volume estimation. When comparing the
four sequences regarding detection of hematomas, the present
study demonstrated that the TIR sequence exhibited the best
segmentability rate. The most accurate results regarding
volume estimation could be achieved with the T1T2w TSE
sequence. In intra- and inter-observer reliability experiments the
TIR and T1T2w TSE sequences showed the most
In general, with all four MR sequences suitable contrast
properties for segmenting hematomas in the subcutaneous
fatty tissue was achieved. Thus, the applicability of the selected
sequences for image segmentation and volume measurement
was shown. A crucial requirement for the choice of the
sequences was to achieve good contrast between the lesion and
the fatty tissue. The contrast achievable between different
tissues is influenced by several factors, with the main factors
Table 3 Number of segmented
hematomas located in the
subcutaneous fatty tissue in
relation to the total number of
artificially created hematomas
located in the subcutaneous fatty
tissue, separately for different
injected blood volumes and MR
MR Magnetic Resonance, FLASH Fast Low Angle Shot, TIR T1 weighted Turbo Inversion Recovery, PDw TSE
FS Proton Density weighted Turbo Spin Echo with fat saturation, T1wT2w TSE T1 and T2 weighted TSE
Fig. 4 Boxplots of ground truth volume plotted against the estimated
hematoma volume. Top: Total hematomas, bottom: hematomas located
only in subcutaneous fatty tissue. Colors represent the MR (Magnetic
Resonance) sequences used for imaging and further segmentation (in
chronological order—pink: FLASH, orange: TIR, brown: PDw TSE
FS, green: T1T2w TSE). Boxes illustrate the median, 25th and 75th
percentiles, and whiskers to lowest/highest data point within a
1.5 × interquartile range, dots represent outliers. The thick black lines
demonstrate the ground truth volumes. (FLASH, Fast Low Angle Shot;
TIR, T1 weighted Turbo Inversion Recovery; PDw TSE FS, Proton
Density weighted Turbo Spin Echo with fat saturation; T1wT2w TSE,
T1 and T2 weighted TSE sequence)
being the relaxation behavior of each tissue. Relaxation times
(T1 and T2) are intrinsic tissue properties which describe the
complex process of nuclear spin magnetization returning to its
equilibrium state following excitation in MRI. Additional
factors relevant in achieving contrast are for example the
magnetic properties (e.g. susceptibility) of tissues and saturation of
specific tissue types (e.g. fat), which is dependent on the
applied MR sequence.
Table 4 Pooled and averaged
results (volumes calculated by
segmentation) of all observers:
median, 25th (Q 0.25) and 75th
(Q 0.75) percentiles of segmented
hematomas located in the
subcutaneous fatty tissue, bold
numbers showing the median
closest to the ground truth
Q Quartile, FLASH Fast Low Angle Shot, TIR T1 weighted Turbo Inversion Recovery, PDw TSE FS Proton
Density weighted Turbo Spin Echo with fat saturation, T1wT2w TSE T1and T2 weighted TSE sequence
Fig. 5 Bland-Altman plot
reliability of one radiologist and
one forensic pathologist for
nontransformed data (left) and
transformed data (right) of
hematomas of the subcutaneous
fatty tissue. The mean hematoma
size is plotted against the
difference in volume estimation.
The black curves represent the
bias, the grey ones the LoA
(Limits of Agreement). Dashed
curves illustrate the 95%
confidence interval of bias (black)
and LoA (grey)
In the gradient echo sequence (FLASH) high contrast was
observed due to the differing magnetic properties of
deoxygenated compared to oxygenated hemoglobin. These intrinsic
tissue properties led to local magnetic field inhomogeneities,
which in turn led to signal loss during the application of this
imaging sequence. The applied turbo inversion recovery
sequence (TIR) allowed nulling of the fat signal at an inversion
time (TI) of 200 ms (3.0 T) based on the characteristically
short T1 of fat. Due to the longer T1 relaxation time of venous
blood, which is a major component in hematomas, the signal
contribution of the lesion was not nulled enabling acquisition
of images with good contrast between the hematoma and the
suppressed fatty tissue. In the proton-density weighted
sequence with fat saturation (PDw TSE FS) a special pulse
was used to abrogate the fat signal, so that contrast between
the lesion and the fatty tissue was once again maximized. In
the sequence with combined T1 and T2 weighting (T1T2w
TSE) the fatty tissue appeared bright due to its short T1 and
Fig. 6 Bland-Altman plot describing intra-observer reliability of
summarized results of transformed data (hematomas located in the
subcutaneous fatty tissue). Brown symbols represent the averaged bias
over the estimated hematoma volumes of each observer, out of two
measurements. The blue symbols represent the LoA (Limits of
Agreement; bias ±1.96 × standard deviation) of the estimated
hematoma volumes of each observer. The boxes represent the median,
25th and 75th percentiles of the averaged data (bias and LoA) over all
observers. The brown continuous curve links the bias averaged over all
four observers (thick black line in boxes), the blue dashed curves link the
averaged LoA of all observers
Fig. 7 Bland-Altman plot describing inter-observer reliability of
summarized results of transformed data (hematomas located in the
subcutaneous fatty tissue). The brown symbols represent the averaged
bias over the estimated hematoma volumes of two observers. The blue
symbols represent the LoA (Limits of Agreement; bias ±1.96 × standard
deviation) of the estimated hematoma volumes of 2 observers. The boxes
represent the median, 25th and 75th percentiles of the averaged data (bias
and LoA) over all calculations. The brown curve links the bias averaged
over all observers (thick black line in boxes), the blue dashed curves link
the averaged LoA of all observers
rather long T2 relaxation time. In comparison, deoxygenated
blood, present in hematomas, appeared darker due to its longer
T1 and shorter T2 relaxation times, once again leading to good
contrast in this sequence.
The contrast between the hematoma located in the muscle
tissue and the actual muscle tissue itself was not adequate.
This was reflected in the results of the segmentability of all
lesions (intramuscular and subcutaneous fatty tissue), which
demonstrated a generally lower segmentation rate. The only
sequence having no location dependency was TIR, where all
hematomas could be segmented independently of their
location. This can be explained by the differences of the T1
relaxation times of the corresponding tissues (fatty tissue: 400 ms,
muscle 900 ms, venous blood: 1500–1650 ms) [35, 36]. The
other sequences did not allow a 100% segmentation rate of all
hematomas but did show increased segmentability, when only
hematomas in fatty tissue were taken into account.
The overall accuracy and precision of the volume
estimat i o n w a s p o o r. Av e r a g e d v o l u m e s w e r e g e n e r a l l y
overestimated, if compared to the injected volume. If
evaluating the lesions inside the fatty tissue only, there was an
increase in accuracy and precision, probably due to the
improved contrast between subcutaneous fatty tissue and blood.
However, the volumes of lesions in the subcutaneous fatty
tissue were still overestimated by all observers, especially by
the radiologist. Over- and underestimation is a general issue in
volume determination using imaging techniques in a medical
context. Huttner et al.  described significant
overestimation of irregularly shaped cerebral hematomas in CT images
using ABC/2 technique for volume estimation. A recent study
by Leddy et al.  noted a significant overestimation of MRI
in volume estimation of breast cancer in contrast to other
imaging modalities. In volume estimation of prostate cancer
using different MR sequences, over- and underestimation of
the actual tumor volume was observed depending on the MR
sequences used, with no single sequence resulting in accurate
tumor volume determination . The volume overestimation
observed in the present study can be explained by several
factors. The inner part of the hematoma (as seen in Fig. 1) is
a compact volume mainly consisting of blood, whereas in the
periphery the blood intermingles with fatty tissue, dispersing
around the fat lobuli and along the septa. The appearance of
this outer area in MR images is dependent on the contrast and
windowing settings. The chosen window parameters have a
great impact on the segmentation results and therefore fixed
window values were introduced in this study. Nevertheless,
the individual perception of hematoma perimeters in MR
images remains a main source of error in manual segmentation.
Another reason for the overestimation of hematoma volumes
might originate from partial volume effects, as a consequence
of the limited voxel size. Especially manual segmentation by
the radiologist in contrast to non-radiologist segmentation
showed extended perimeters of the hematoma. Interestingly,
the sequence where the least hematomas were segmented
(T1T2w TSE) was the most accurate one concerning volume
estimation. In the T1T2w TSE sequence fatty tissue structures
were visible within some hematomas, which were not visible
in the other sequences (Fig. 3), additionally leading to a better
defined differentiation of the hematomas. Another effect on
volume estimation could also be attributed to image
resolution, which was higher for the T1T2w TSE and PDw TSE FS
sequences than for the FLASH and TIR sequences. However,
this effect was more prominent for the T1T2w TSE sequence.
A decreasing relative error for all observers was observed
with increasing hematoma size. This can be explained by the
physical model used to normalize the data. By assuming a
hematoma of spherical form, the resulting error due to
oversegmentation decreases with increasing hematoma radius. In
this study, very small amounts of blood were examined.
However, under in vivo conditions usually larger hematoma
volumes would be expected, which would reduce this relative
error. These factors which contributed to the volume
overestimation can also be held accountable for the low intra- and
inter-observer reliability obtained in this study.
One limitation of this study was that for some hematomas
residual blood flowed out of the injection canal or was not
completely injected leading to minor errors in the ground
truth. Additionally, the acquisition protocols were optimized
for achieving good contrast between blood and fatty tissue.
Therefore, blood in muscle tissue was not optimally depicted.
In conclusion, this study demonstrates the potential of MRI
to visualize even very small amounts of blood in subcutaneous
fatty tissue. Hematomas were in general well segmentable in
all of the applied sequences, with the TIR sequence showing
the best segmentation rate independent of the location of the
hematomas. Concerning volume estimation, the T1T2w TSE
sequence was most accurate. Overall, the TIR and T1T2w
TSE sequences were identified as the sequences with the
highest potential for hematoma detection and volume
estimation – even for very small hemorrhages.
In future, these results can be used to improve MR
protocols for hematoma detection in both, forensically and
clinically relevant cases. Therefore, this study provides the first step
to optimize clinical forensic imaging using MRI, especially in
cases where objective evidence of subcutaneous hematomas is
1. Reliable characterization of hematomas in the subcutane
ous fatty tissue is necessary for the forensic reconstruction
in cases of interpersonal violence or child maltreatment.
2. Four magnetic resonance sequences (FLASH, TIR, PDw
TSE FS, T1T2w TSE) were evaluated with respect to the
contrast between hematoma and subcutaneous fatty tissue
and volume estimation of artificial hematomas in a
porcine tissue model.
3. The TIR sequence exhibited the best segmentability rate
and the T1T2w TSE sequence showed the most accurate
results regarding volume estimation.
4. Segmentation and volume estimation of artificial hemato
mas of various sizes (0.1–1 mL) were successfully
achieved using MRI.
Acknowledgements Open access funding provided by Medical
University of Graz. The authors gratefully thank Bridgette Webb, MSc,
and Thomas Widek, MSc, of the Ludwig Boltzmann Institute for
Clinical-Forensic Imaging, for technical assistance and critical review
of the manuscript.
Compliance with ethical standards
Ethical approval All procedures performed in studies involving
human participants were in accordance with the ethical standards of the
institutional and/or national research committee and with the 1964
Helsinki declaration and its later amendments or comparable ethical
All applicable international, national, and/or institutional guidelines
for the care and use of animals were followed.
Informed consent Informed consent was obtained from all individual
participants included in the study.
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