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controller design software  (MathWorks Inc)


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    Structured Review

    MathWorks Inc controller design software
    Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for <t>controller</t> feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.
    Controller Design Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 873 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/controller design software/product/MathWorks Inc
    Average 96 stars, based on 873 article reviews
    controller design software - by Bioz Stars, 2026-04
    96/100 stars

    Images

    1) Product Images from "Automated laser retraction for targeted glioblastoma coverage during laser interstitial thermal therapy"

    Article Title: Automated laser retraction for targeted glioblastoma coverage during laser interstitial thermal therapy

    Journal: Medical Physics

    doi: 10.1002/mp.70267

    Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for controller feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.
    Figure Legend Snippet: Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for controller feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.

    Techniques Used:

    Block diagram of cascaded proportional integral derivative (PID) fuzzy logic controller for thermal damage control during MRgLITT treatments.
    Figure Legend Snippet: Block diagram of cascaded proportional integral derivative (PID) fuzzy logic controller for thermal damage control during MRgLITT treatments.

    Techniques Used: Blocking Assay, Control

    PID controller with automatic probe retraction for COP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.
    Figure Legend Snippet: PID controller with automatic probe retraction for COP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.

    Techniques Used:

    PID controller with automatic probe retraction for VOP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.
    Figure Legend Snippet: PID controller with automatic probe retraction for VOP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.

    Techniques Used:



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    Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for <t>controller</t> feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.
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    Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for <t>controller</t> feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.
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    Image Search Results


    Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for controller feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.

    Journal: Medical Physics

    Article Title: Automated laser retraction for targeted glioblastoma coverage during laser interstitial thermal therapy

    doi: 10.1002/mp.70267

    Figure Lengend Snippet: Geometry and laser log obtained from de‐identified patient dataset, demonstrating probe placement for controller feedback. (a) Three‐dimensional human head geometry, obtained from a de‐identified magnetic resonance guided laser interstitial thermal therapy (MRgLITT) patient, was segmented from MR images. This geometry was partitioned into five distinct domains, representing the skull, cerebrospinal fluid (CSF) general, brain tissue (averaged white matter and gray matter), CSF ventricles, and the tumor region along with MNP distribution. (b) The laser power and incremental laser retraction (5 mm) were modeled using a laser log from the de‐identified MRgLITT treatment. (c) Placement of temperature and thermal damage measuring probes within the tumor to provide feedback to the controller. L1, L2, and L3 represent the incremental laser retraction. CP1, CP2 and CP3 represent the maximum tumor temperature, whereas BP1, BP2, and BP3 represent the tumor boundary temperature.

    Article Snippet: Controller design software such as MATLAB Simulink allows for the design of linear temporal models but lacks the capability to accurately represent the spatiotemporal dynamics of the system which will lead to suboptimal treatment plan.

    Techniques:

    Block diagram of cascaded proportional integral derivative (PID) fuzzy logic controller for thermal damage control during MRgLITT treatments.

    Journal: Medical Physics

    Article Title: Automated laser retraction for targeted glioblastoma coverage during laser interstitial thermal therapy

    doi: 10.1002/mp.70267

    Figure Lengend Snippet: Block diagram of cascaded proportional integral derivative (PID) fuzzy logic controller for thermal damage control during MRgLITT treatments.

    Article Snippet: Controller design software such as MATLAB Simulink allows for the design of linear temporal models but lacks the capability to accurately represent the spatiotemporal dynamics of the system which will lead to suboptimal treatment plan.

    Techniques: Blocking Assay, Control

    PID controller with automatic probe retraction for COP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.

    Journal: Medical Physics

    Article Title: Automated laser retraction for targeted glioblastoma coverage during laser interstitial thermal therapy

    doi: 10.1002/mp.70267

    Figure Lengend Snippet: PID controller with automatic probe retraction for COP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.

    Article Snippet: Controller design software such as MATLAB Simulink allows for the design of linear temporal models but lacks the capability to accurately represent the spatiotemporal dynamics of the system which will lead to suboptimal treatment plan.

    Techniques:

    PID controller with automatic probe retraction for VOP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.

    Journal: Medical Physics

    Article Title: Automated laser retraction for targeted glioblastoma coverage during laser interstitial thermal therapy

    doi: 10.1002/mp.70267

    Figure Lengend Snippet: PID controller with automatic probe retraction for VOP. (a) Power. (b) Temperature at CP. (c) Temperature at BP. (d) Thermal damage at BP. (e) Temperature contour of 60 and 43°C at the end of L1, L2, and L3 respectively.

    Article Snippet: Controller design software such as MATLAB Simulink allows for the design of linear temporal models but lacks the capability to accurately represent the spatiotemporal dynamics of the system which will lead to suboptimal treatment plan.

    Techniques: