In this work, we study the strong decays of the newly observed
Ξ
(
1620
)
0
assuming that it is a meson-baryon molecular state of
Λ
K
¯
and
Σ
K
¯
. We consider four possible spin-parity assignments
J
...P
=
1
/
2
±
and
3
/
2
±
for the
Ξ
(
1620
)
0
, and evaluate its partial decay width into
Ξ
π
and
Ξ
π
π
via hadronic loops with the help of effective Lagrangians. In comparison with the Belle data, the calculated decay width favors the spin-party assignment
1
/
2
-
while the other spin-parity assignments do not yield a decay width consistent with data in the molecule picture. We find that about 52–68% of the total width comes from the
K
¯
Λ
channel, while the rest is provided by the
K
¯
Σ
channel. As a result, both channels are important in explaining the strong decay of the
Ξ
(
1620
)
0
. In addition, the transition
Ξ
(
1620
)
0
→
π
Ξ
is the main decay channel in the
J
P
=
1
/
2
-
case, which almost saturates the total width. These information are helpful to further understand the nature of the
Ξ
(
1620
)
0
.
...there is no guarantee that the dose delivered to the patient is the same as planned, due to the patient's anatomical change, setup uncertainty, and organ motion during treatments. ...in vivo ...dosimetry (IVD) has been recommended as part of routine IMRT to monitor the actual dose delivered to the patient, detect the source of errors, and assist in adaptive therapy. ...a method that can quickly detect and classify the error source is highly desirable and needed. ...it is difficult to obtain anatomical error data from actual treatment to set the "ground truth" to train and test ML/DL models. ...the proposed ML/DL models in existing studies are based entirely on simulations, which have limited applicability to the real situation. ...the error classification system based on ML/DL models can only identify those errors in relation to which they have been trained.
•The first study on commission and clinical implementation of AI model for IMRT QA.•The biggest multi-institution dataset for AI model training/validation and test.•An executable QA program was ...proposed for the AI-based IMRT QA for the first time.•This study proved the AI model can be used for IMRT QA clinically.•A classification-regression integrated AI model developed with better performance.
To commission and implement an Autoencoder based Classification-Regression (ACLR) model for VMAT patient-specific quality assurance (PSQA) in a multi-institution scenario.
1835 VMAT plans from seven institutions were collected for the ACLR model commissioning and multi-institutional validation. We established three scenarios to validate the gamma passing rates (GPRs) prediction and classification accuracy with the ACLR model for different delivery equipment, QA devices, and treatment planning systems (TPS). The prediction performance of the ACLR model was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The classification performance was evaluated using sensitivity and specificity. An independent end-to-end test (E2E) and routine QA of the ACLR model were performed to validate the clinical use of the model.
For multi-institution validations, the MAEs were 1.30–2.80% and 2.42–4.60% at 3%/3 mm and 3%/2 mm, respectively, and RMSEs were 1.55–2.98% and 2.83–4.95% at 3%/3 mm and 3%/2 mm, respectively, with different delivery equipment, QA devices, and TPS, while the sensitivity was 90% and specificity was 70.1% at 3%/2 mm. For the E2E, the deviations between the predicted and measured results were within 3%, and the model passed the consistency check for clinical implementation. The predicted results of the model were the same in daily QA, while the deviations between the repeated monthly measured GPRs were all within 2%.
The performance of the ACLR model in multi-institution scenarios was validated on a large scale. Routine QA of the ACLR model was established and the model could be used for VMAT PSQA clinically.
Purpose: To develop a deep learning framework based on a hybrid dataset to enhance the quality of CBCT images and obtain accurate HU values. Materials and Methods: A total of 228 cervical cancer ...patients treated in different LINACs were enrolled. We developed an encoder–decoder architecture with residual learning and skip connections. The model was hierarchically trained and validated on 5279 paired CBCT/planning CT images and tested on 1302 paired images. The mean absolute error (MAE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM) were utilized to access the quality of the synthetic CT images generated by our model. Results: The MAE between synthetic CT images generated by our model and planning CT was 10.93 HU, compared to 50.02 HU for the CBCT images. The PSNR increased from 27.79 dB to 33.91 dB, and the SSIM increased from 0.76 to 0.90. Compared with synthetic CT images generated by the convolution neural networks with residual blocks, our model had superior performance both in qualitative and quantitative aspects. Conclusions: Our model could synthesize CT images with enhanced image quality and accurate HU values. The synthetic CT images preserved the edges of tissues well, which is important for downstream tasks in adaptive radiotherapy.
Abstract In this work, we study the strong decays of the newly observed $$\varXi (1620)^0$$ Ξ ( 1620 ) 0 assuming that it is a meson-baryon molecular state of $$\varLambda {\bar{K}}$$ Λ K ¯ and ...$$\varSigma {\bar{K}}$$ Σ K ¯ . We consider four possible spin-parity assignments $$J^P=1/2^{\pm }$$ J P = 1 / 2 ± and $$3/2^{\pm }$$ 3 / 2 ± for the $$\varXi (1620)^0$$ Ξ ( 1620 ) 0 , and evaluate its partial decay width into $$\varXi \pi $$ Ξ π and $$\varXi \pi \pi $$ Ξ π π via hadronic loops with the help of effective Lagrangians. In comparison with the Belle data, the calculated decay width favors the spin-party assignment $$1/2^-$$ 1 / 2 - while the other spin-parity assignments do not yield a decay width consistent with data in the molecule picture. We find that about 52–68% of the total width comes from the $${\bar{K}}\varLambda $$ K ¯ Λ channel, while the rest is provided by the $${\bar{K}}\varSigma $$ K ¯ Σ channel. As a result, both channels are important in explaining the strong decay of the $$\varXi (1620)^0$$ Ξ ( 1620 ) 0 . In addition, the transition $$\varXi (1620)^0\rightarrow \pi \varXi $$ Ξ ( 1620 ) 0 → π Ξ is the main decay channel in the $$J^{P}=1/2^{-}$$ J P = 1 / 2 - case, which almost saturates the total width. These information are helpful to further understand the nature of the $$\varXi (1620)^0$$ Ξ ( 1620 ) 0 .
Abstract
In this work, we study the strong decays of the newly observed
$$\varXi (1620)^0$$
Ξ
(
1620
)
0
assuming that it is a meson-baryon molecular state of
$$\varLambda {\bar{K}}$$
Λ
K
¯
and
...$$\varSigma {\bar{K}}$$
Σ
K
¯
. We consider four possible spin-parity assignments
$$J^P=1/2^{\pm }$$
J
P
=
1
/
2
±
and
$$3/2^{\pm }$$
3
/
2
±
for the
$$\varXi (1620)^0$$
Ξ
(
1620
)
0
, and evaluate its partial decay width into
$$\varXi \pi $$
Ξ
π
and
$$\varXi \pi \pi $$
Ξ
π
π
via hadronic loops with the help of effective Lagrangians. In comparison with the Belle data, the calculated decay width favors the spin-party assignment
$$1/2^-$$
1
/
2
-
while the other spin-parity assignments do not yield a decay width consistent with data in the molecule picture. We find that about 52–68% of the total width comes from the
$${\bar{K}}\varLambda $$
K
¯
Λ
channel, while the rest is provided by the
$${\bar{K}}\varSigma $$
K
¯
Σ
channel. As a result, both channels are important in explaining the strong decay of the
$$\varXi (1620)^0$$
Ξ
(
1620
)
0
. In addition, the transition
$$\varXi (1620)^0\rightarrow \pi \varXi $$
Ξ
(
1620
)
0
→
π
Ξ
is the main decay channel in the
$$J^{P}=1/2^{-}$$
J
P
=
1
/
2
-
case, which almost saturates the total width. These information are helpful to further understand the nature of the
$$\varXi (1620)^0$$
Ξ
(
1620
)
0
.
In this work, we study the strong decays of the newly observed Formula omitted assuming that it is a meson-baryon molecular state of Formula omitted and Formula omitted. We consider four possible ...spin-parity assignments Formula omitted and Formula omitted for the Formula omitted, and evaluate its partial decay width into Formula omitted and Formula omitted via hadronic loops with the help of effective Lagrangians. In comparison with the Belle data, the calculated decay width favors the spin-party assignment Formula omitted while the other spin-parity assignments do not yield a decay width consistent with data in the molecule picture. We find that about 52-68% of the total width comes from the Formula omitted channel, while the rest is provided by the Formula omitted channel. As a result, both channels are important in explaining the strong decay of the Formula omitted. In addition, the transition Formula omitted is the main decay channel in the Formula omitted case, which almost saturates the total width. These information are helpful to further understand the nature of the Formula omitted.
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