diff --git a/code/nnv/engine/nn/layers/FullyConnectedLayer.m b/code/nnv/engine/nn/layers/FullyConnectedLayer.m
index fd960f61e9..b2d07ce997 100644
--- a/code/nnv/engine/nn/layers/FullyConnectedLayer.m
+++ b/code/nnv/engine/nn/layers/FullyConnectedLayer.m
@@ -284,15 +284,8 @@
                            
                 n = in_image.numPred;
                 V(1, 1, :, in_image.numPred + 1) = zeros(obj.OutputSize, 1, 'like', in_image.V);
-                for i=1:n+1
-                    I = in_image.V(:,:,:,i);
-                    I = reshape(I,N,1); % flatten input
-                    if i==1
-                        V(1, 1,:,i) = obj.Weights*I + obj.Bias;
-                    else
-                        V(1, 1,:,i) = obj.Weights*I;
-                    end
-                end
+                V(1, 1, :, :) = obj.Weights*reshape(in_image.V, N, n + 1);
+                V(1, 1, :, 1) = reshape(V(1, 1, :, 1), obj.OutputSize, 1) + obj.Bias;
                 % output set
                 image = ImageStar(V, in_image.C, in_image.d, in_image.pred_lb, in_image.pred_ub);
             else % reach Star set
diff --git a/code/nnv/engine/nn/layers/ImageInputLayer.m b/code/nnv/engine/nn/layers/ImageInputLayer.m
index 8e923501b3..98f16379a7 100644
--- a/code/nnv/engine/nn/layers/ImageInputLayer.m
+++ b/code/nnv/engine/nn/layers/ImageInputLayer.m
@@ -116,6 +116,12 @@
                 image = in_image;
             elseif strcmp(obj.Normalization, 'zerocenter')
                 image = in_image.affineMap([], -obj.Mean);
+            elseif strcmp(obj.Normalization, 'zscore')
+                image = in_image.affineMap([], -obj.Mean);
+                layer_std = obj.StandardDeviation;
+                for nc = 1:image.numChannel
+                    image.V(:,:,nc,:) = image.V(:,:,nc,:)/layer_std(nc);
+                end
             else
                 error('The normalization method is not supported yet.')
             end
diff --git a/code/nnv/engine/set/Box.m b/code/nnv/engine/set/Box.m
index 3dc872f52f..f36580ccca 100644
--- a/code/nnv/engine/set/Box.m
+++ b/code/nnv/engine/set/Box.m
@@ -40,7 +40,7 @@
                 % Speeding up implementation
                 gens = diag(vec); % generate matrix
                 if numel(gens) > 1
-                    gens(:,all(gens(gens==0))) = []; % delete colums with no info
+                    gens(:,all(gens==0)) = []; % delete colums with no info
                 end
                 obj.generators = gens;
             catch
diff --git a/code/nnv/engine/set/VolumeStar.m b/code/nnv/engine/set/VolumeStar.m
index bbda1ac899..390a540695 100644
--- a/code/nnv/engine/set/VolumeStar.m
+++ b/code/nnv/engine/set/VolumeStar.m
@@ -554,16 +554,16 @@
                 S.V = gather(S.V);
                 S.C = gather(S.C);
                 S.d = gather(S.d);
-                S.predicate_lb = gather(S.predicate_lb); 
-                S.predicate_ub = gather(S.predicate_ub);
+                S.pred_lb = gather(S.pred_lb); 
+                S.pred_ub = gather(S.pred_ub);
                 S.vol_lb = gather(S.vol_lb); 
                 S.vol_ub = gather(S.vol_ub);
             elseif strcmp(deviceTarget, 'gpu')
                 S.V = gpuArray(S.V);
                 S.C = gpuArray(S.C);
                 S.d = gpuArray(S.d);
-                S.predicate_lb = gpuArray(S.predicate_lb); 
-                S.predicate_ub = gpuArray(S.predicate_ub);
+                S.pred_lb = gpuArray(S.pred_lb); 
+                S.pred_ub = gpuArray(S.pred_ub);
                 S.vol_lb = gpuArray(S.vol_lb); 
                 S.vol_ub = gpuArray(S.vol_ub);
             else
diff --git a/code/nnv/engine/utils/lpsolver.m b/code/nnv/engine/utils/lpsolver.m
index ccde224ead..41c320658c 100644
--- a/code/nnv/engine/utils/lpsolver.m
+++ b/code/nnv/engine/utils/lpsolver.m
@@ -49,8 +49,8 @@
         % Define solver parameters
         params = struct; % for now, leave default options/params
         params.OutputFlag = 0; % no display
-        params.OptimalityTol = 1e-09;
-        params.FeasibilityTol = 1e-09;
+        % params.OptimalityTol = 1e-09;
+        % params.FeasibilityTol = 1e-09;
         result = gurobi(model, params);
         fval = result.objval; % get fval value from results
         % get exitflag and match those of linprog for easier parsing
diff --git a/code/nnv/engine/utils/verify_specification.m b/code/nnv/engine/utils/verify_specification.m
index 0de36f7193..e6af98b1bc 100644
--- a/code/nnv/engine/utils/verify_specification.m
+++ b/code/nnv/engine/utils/verify_specification.m
@@ -32,6 +32,9 @@
             if ~isa(Set, "Star")
                 Set = Set.toStar;
             end
+            if isa(Set.V, 'gpuArray')
+                Set = Set.changeDevice('cpu');
+            end
             S = Set.intersectHalfSpace(property.G, property.g); % compute intersection with unsafe/not robust region
             if isempty(S)
                 result = 1; % no intersection with unsafe region = safe (unsat)
@@ -57,6 +60,7 @@
                     continue; % does nothing, just need an statement, wanted to make this clear
                 else
                     result = 2; %  unknown if approx, sat if exact
+                    return;
                 end
             end
             cp = cp+1;
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diff --git a/code/nnv/examples/Submission/WiP_3d/run_all.m b/code/nnv/examples/Submission/WiP_3d/run_all.m
index 6ff562bd3b..3ebff61697 100644
--- a/code/nnv/examples/Submission/WiP_3d/run_all.m
+++ b/code/nnv/examples/Submission/WiP_3d/run_all.m
@@ -1,31 +1,52 @@
-%% Shape only data (3d)
+% %% Shape only data (3d)
+% 
+% disp("... adrenal ...");
+% verify_adrenal;
+% 
+% disp("... vessel ...");
+% verify_vessel;
+% 
+% 
+% %% Volume data (general 3D)
+% 
+% 
+% disp("... fracture ...");
+% verify_fracture;
+% 
+% 
+% disp("... nodule ...")
+% verify_nodule;
+% 
+% 
+% disp("... organ ...")
+% verify_organ;
+% 
+% 
+% disp("... synapse ...")
+% verify_synapse;
+
+
+% disp("... Creating plots...");
+% visualize_results_gen;
+% visualize_results_shape;
+
+
+%% GPU
 
 disp("... adrenal ...");
-verify_adrenal;
+verify_adrenal_gpu;
 
 disp("... vessel ...");
-verify_vessel;
-
-
-%% Volume data (general 3D)
-
+verify_vessel_gpu;
 
 disp("... fracture ...");
-verify_fracture;
-
+verify_fracture_gpu;
 
 disp("... nodule ...")
-verify_nodule;
-
+verify_nodule_gpu;
 
 disp("... organ ...")
-verify_organ;
-
+verify_organ_gpu;
 
 disp("... synapse ...")
-verify_synapse;
-
-
-disp("... Creating plots...");
-visualize_results_gen;
-visualize_results_shape;
+verify_synapse_gpu;
\ No newline at end of file
diff --git a/code/nnv/examples/Submission/WiP_3d/verify_adrenal_gpu.m b/code/nnv/examples/Submission/WiP_3d/verify_adrenal_gpu.m
new file mode 100644
index 0000000000..1a5af828f8
--- /dev/null
+++ b/code/nnv/examples/Submission/WiP_3d/verify_adrenal_gpu.m
@@ -0,0 +1,82 @@
+%% Verify adrenal dataset
+% adrenalMNIST3D, input size: 28x28x28
+
+% Data
+dataset = "../../../../../data/medmnist/mat_files/adrenalmnist3d.mat"; % path to data
+modelpath = "../../../../../data/medmnist/models/model_adrenalmnist3d.mat";
+
+disp("Begin verification of adrenal3d");
+
+% Load data
+load(dataset);
+
+% data to verify (test set)
+test_images = squeeze(permute(test_images, [2 3 4 5 1]));
+test_labels = test_labels + 1;
+
+% load network
+load(modelpath);
+matlabNet = net;
+net = matlab2nnv(net);
+
+% select volumes to verify
+N = 50;
+idxs = zeros(N,1);
+count = 1;
+
+for i = 1:length(test_labels)
+    y = classify(matlabNet,test_images(:,:,:,i));
+    if single(y) == test_labels(i)
+        idxs(count) = i;
+        count = count + 1;
+    end
+    if count > N
+        break
+    end
+end
+
+inputs = single(test_images(:,:,:,idxs));
+targets = single(test_labels(idxs));
+
+% Reachability parameters
+reachOptions = struct;
+reachOptions.reachMethod = 'relax-star-area';
+reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
+reachOptions.device = 'gpu';
+
+
+% Study variables
+advType = ["add", "remove"];
+maxpixels = [50, 100, 500, 1000]; %out of 28x28x28 pixels
+% maxpixels = 1000;
+epsilon = 1; % ep / 255
+
+
+%% Verification analysis
+for a=advType
+    for mp=maxpixels
+        for ep=epsilon
+            
+            % 1) Initialize results var
+            results = zeros(N,2);
+            
+            % 2) Create adversarial attack
+            adv_attack = struct;
+            adv_attack.Name = a; % add or remove
+            adv_attack.max_pixels = mp; % Max number of pixels to modify from input image
+            adv_attack.noise_de = ep/255; % disturbance (noise) on pixels
+            
+            % 3) Begin verification analysis
+            for i=1:N
+                img = inputs(:,:,:,i);
+                target = targets(i);
+                results(i,:) = verify_instance_shape(net, img, target, adv_attack, reachOptions);
+            end
+            
+            % 4) % save results
+            save("resultsGPU/verification_adrenal_"+ a +"_" + ep +"_" + mp + ".mat", "results");
+
+        end
+    end
+end
\ No newline at end of file
diff --git a/code/nnv/examples/Submission/WiP_3d/verify_fracture_gpu.m b/code/nnv/examples/Submission/WiP_3d/verify_fracture_gpu.m
new file mode 100644
index 0000000000..fafc9f81fc
--- /dev/null
+++ b/code/nnv/examples/Submission/WiP_3d/verify_fracture_gpu.m
@@ -0,0 +1,86 @@
+%% Verify fracture dataset
+% VesselMNIST3D, input size: 28x28x28
+
+% Data
+dataset = "../../../../../data/medmnist/mat_files/fracturemnist3d.mat"; % path to data
+modelpath = "../../../../../data/medmnist/models/model_fracturemnist3d.mat";
+
+disp("Begin verification of fracture3d");
+
+% Load data
+load(dataset);
+
+% data to verify (test set)
+test_images = permute(test_images, [2 3 4 5 1]);
+test_labels = test_labels + 1;
+
+% load network
+load(modelpath);
+matlabNet = net;
+net = matlab2nnv(net);
+
+% select volumes to verify
+N = 50;
+idxs = zeros(N,1);
+count = 1;
+
+for i = 1:length(test_labels)
+    y = classify(matlabNet,test_images(:,:,:,i));
+    if single(y) == test_labels(i)
+        idxs(count) = i;
+        count = count + 1;
+    end
+    if count > N
+        break
+    end
+end
+
+inputs = single(test_images(:,:,:,idxs));
+targets = single(test_labels(idxs));
+
+% Reachability parameters
+reachOptions = struct;
+reachOptions.reachMethod = 'relax-star-area';
+reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
+reachOptions.device = 'gpu';
+
+
+% Study variables
+advType = ["bright", "dark"];
+maxpixels = [50, 100, 500, 1000]; %out of 28x28x28 pixels
+epsilon = [2, 5, 10, 25]; % ep / 255
+threshold = [100; 150]; % bright ; dark
+
+%% Verification analysis
+for a=advType
+    for mp=maxpixels
+        for ep=epsilon
+            
+            % 1) Initialize results var
+            results = zeros(N,2);
+            
+            % 2) Create adversarial attack
+            adv_attack = struct;
+            adv_attack.Name = a; % bright or dark
+            if strcmp(a, "bright") 
+                adv_attack.threshold = threshold(1); % perturb pixels below this value
+            else 
+                adv_attack.threshold = threshold(2); % perturb pixels below this value
+            end 
+            adv_attack.max_pixels = mp; % Max number of pixels to modify from input image
+            adv_attack.noise_de = ep/255; % disturbance (noise) on pixels
+            
+            % 3) Begin verification analysis
+            for i=1:N
+                img = inputs(:,:,:,i);
+                target = targets(i);
+                results(i,:) = verify_instance_3d(net, img, target, adv_attack, reachOptions);
+            end
+            
+            % 4) % save results
+            save("resultsGPU/verification_fracture_"+ a +"_" + ep +"_" + mp + ".mat", "results");
+
+        end
+    end
+end
\ No newline at end of file
diff --git a/code/nnv/examples/Submission/WiP_3d/verify_nodule_gpu.m b/code/nnv/examples/Submission/WiP_3d/verify_nodule_gpu.m
new file mode 100644
index 0000000000..c034292d5a
--- /dev/null
+++ b/code/nnv/examples/Submission/WiP_3d/verify_nodule_gpu.m
@@ -0,0 +1,86 @@
+%% Verify nodule dataset
+% NoduleMNIST3D, input size: 28x28x28
+
+% Data
+dataset = "../../../../../data/medmnist/mat_files/nodulemnist3d.mat"; % path to data
+modelpath = "../../../../../data/medmnist/models/model_nodulemnist3d.mat";
+
+disp("Begin verification of nodule3d");
+
+% Load data
+load(dataset);
+
+% data to verify (test set)
+test_images = permute(test_images, [2 3 4 5 1]);
+test_labels = test_labels + 1;
+
+% load network
+load(modelpath);
+matlabNet = net;
+net = matlab2nnv(net);
+
+% select volumes to verify
+N = 50;
+idxs = zeros(N,1);
+count = 1;
+
+for i = 1:length(test_labels)
+    y = classify(matlabNet,test_images(:,:,:,i));
+    if single(y) == test_labels(i)
+        idxs(count) = i;
+        count = count + 1;
+    end
+    if count > N
+        break
+    end
+end
+
+inputs = single(test_images(:,:,:,idxs));
+targets = single(test_labels(idxs));
+
+% Reachability parameters
+reachOptions = struct;
+reachOptions.reachMethod = 'relax-star-area';
+reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
+reachOptions.device = 'gpu';
+
+
+% Study variables
+advType = ["bright", "dark"];
+maxpixels = [50, 100, 500, 1000]; %out of 28x28x28 pixels
+epsilon = [2, 5, 10, 25]; % ep / 255
+threshold = [100; 150]; % bright ; dark
+
+%% Verification analysis
+for a=advType
+    for mp=maxpixels
+        for ep=epsilon
+            
+            % 1) Initialize results var
+            results = zeros(N,2);
+            
+            % 2) Create adversarial attack
+            adv_attack = struct;
+            adv_attack.Name = a; % bright or dark
+            if strcmp(a, "bright") 
+                adv_attack.threshold = threshold(1); % perturb pixels below this value
+            else 
+                adv_attack.threshold = threshold(2); % perturb pixels below this value
+            end 
+            adv_attack.max_pixels = mp; % Max number of pixels to modify from input image
+            adv_attack.noise_de = ep/255; % disturbance (noise) on pixels
+            
+            % 3) Begin verification analysis
+            for i=1:N
+                img = inputs(:,:,:,i);
+                target = targets(i);
+                results(i,:) = verify_instance_3d(net, img, target, adv_attack, reachOptions);
+            end
+            
+            % 4) % save results
+            save("resultsGPU/verification_nodule_"+ a +"_" + ep +"_" + mp + ".mat", "results");
+
+        end
+    end
+end
\ No newline at end of file
diff --git a/code/nnv/examples/Submission/WiP_3d/verify_organ_gpu.m b/code/nnv/examples/Submission/WiP_3d/verify_organ_gpu.m
new file mode 100644
index 0000000000..b9aaa60834
--- /dev/null
+++ b/code/nnv/examples/Submission/WiP_3d/verify_organ_gpu.m
@@ -0,0 +1,85 @@
+%% Verify organ dataset
+% VesselMNIST3D, input size: 28x28x28
+
+% Data
+dataset = "../../../../../data/medmnist/mat_files/organmnist3d.mat"; % path to data
+modelpath = "../../../../../data/medmnist/models/model_organmnist3d.mat";
+
+disp("Begin verification of organ3d");
+
+% Load data
+load(dataset);
+
+% data to verify (test set)
+test_images = permute(test_images, [2 3 4 5 1]);
+test_labels = test_labels + 1;
+
+% load network
+load(modelpath);
+matlabNet = net;
+net = matlab2nnv(net);
+
+% select volumes to verify
+N = 50;
+idxs = zeros(N,1);
+count = 1;
+
+for i = 1:length(test_labels)
+    y = classify(matlabNet,test_images(:,:,:,i));
+    if single(y) == test_labels(i)
+        idxs(count) = i;
+        count = count + 1;
+    end
+    if count > N
+        break
+    end
+end
+
+inputs = single(test_images(:,:,:,idxs));
+targets = single(test_labels(idxs));
+
+% Reachability parameters
+reachOptions = struct;
+reachOptions.reachMethod = 'relax-star-area';
+reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
+reachOptions.device = 'gpu';
+
+% Study variables
+advType = ["bright", "dark"];
+maxpixels = [50, 100, 500, 1000]; %out of 28x28x28 pixels
+epsilon = [2, 5, 10, 25]; % ep / 255
+threshold = [100; 150]; % bright ; dark
+
+%% Verification analysis
+for a=advType
+    for mp=maxpixels
+        for ep=epsilon
+            
+            % 1) Initialize results var
+            results = zeros(N,2);
+            
+            % 2) Create adversarial attack
+            adv_attack = struct;
+            adv_attack.Name = a; % bright or dark
+            if strcmp(a, "bright") 
+                adv_attack.threshold = threshold(1); % perturb pixels below this value
+            else 
+                adv_attack.threshold = threshold(2); % perturb pixels below this value
+            end 
+            adv_attack.max_pixels = mp; % Max number of pixels to modify from input image
+            adv_attack.noise_de = ep/255; % disturbance (noise) on pixels
+            
+            % 3) Begin verification analysis
+            for i=1:N
+                img = inputs(:,:,:,i);
+                target = targets(i);
+                results(i,:) = verify_instance_3d(net, img, target, adv_attack, reachOptions);
+            end
+            
+            % 4) % save results
+            save("resultsGPU/verification_organ_"+ a +"_" + ep +"_" + mp + ".mat", "results");
+
+        end
+    end
+end
\ No newline at end of file
diff --git a/code/nnv/examples/Submission/WiP_3d/verify_synapse_gpu.m b/code/nnv/examples/Submission/WiP_3d/verify_synapse_gpu.m
new file mode 100644
index 0000000000..eaafd76e6f
--- /dev/null
+++ b/code/nnv/examples/Submission/WiP_3d/verify_synapse_gpu.m
@@ -0,0 +1,86 @@
+%% Verify synapse dataset
+% SynapseMNIST3D, input size: 28x28x28
+
+% Data
+dataset = "../../../../../data/medmnist/mat_files/synapsemnist3d.mat"; % path to data
+modelpath = "../../../../../data/medmnist/models/model_synapsemnist3d.mat";
+
+disp("Begin verification of synapse3d");
+
+% Load data
+load(dataset);
+
+% data to verify (test set)
+test_images = permute(test_images, [2 3 4 5 1]);
+test_labels = test_labels + 1;
+
+% load network
+load(modelpath);
+matlabNet = net;
+net = matlab2nnv(net);
+
+% select volumes to verify
+N = 50;
+idxs = zeros(N,1);
+count = 1;
+
+for i = 1:length(test_labels)
+    y = classify(matlabNet,test_images(:,:,:,i));
+    if single(y) == test_labels(i)
+        idxs(count) = i;
+        count = count + 1;
+    end
+    if count > N
+        break
+    end
+end
+
+inputs = single(test_images(:,:,:,idxs));
+targets = single(test_labels(idxs));
+
+% Reachability parameters
+reachOptions = struct;
+reachOptions.reachMethod = 'relax-star-area';
+reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
+reachOptions.device = 'gpu';
+
+
+% Study variables
+advType = ["bright", "dark"];
+maxpixels = [50, 100, 500, 1000]; %out of 28x28x28 pixels
+epsilon = [2, 5, 10, 25]; % ep / 255
+threshold = [100; 150]; % bright ; dark
+
+%% Verification analysis
+for a=advType
+    for mp=maxpixels
+        for ep=epsilon
+            
+            % 1) Initialize results var
+            results = zeros(N,2);
+            
+            % 2) Create adversarial attack
+            adv_attack = struct;
+            adv_attack.Name = a; % bright or dark
+            if strcmp(a, "bright") 
+                adv_attack.threshold = threshold(1); % perturb pixels below this value
+            else 
+                adv_attack.threshold = threshold(2); % perturb pixels below this value
+            end 
+            adv_attack.max_pixels = mp; % Max number of pixels to modify from input image
+            adv_attack.noise_de = ep/255; % disturbance (noise) on pixels
+            
+            % 3) Begin verification analysis
+            for i=1:N
+                img = inputs(:,:,:,i);
+                target = targets(i);
+                results(i,:) = verify_instance_3d(net, img, target, adv_attack, reachOptions);
+            end
+            
+            % 4) % save results
+            save("resultsGPU/verification_synapse_"+ a +"_" + ep +"_" + mp + ".mat", "results");
+
+        end
+    end
+end
\ No newline at end of file
diff --git a/code/nnv/examples/Submission/WiP_3d/verify_vessel_gpu.m b/code/nnv/examples/Submission/WiP_3d/verify_vessel_gpu.m
new file mode 100644
index 0000000000..3025d0ad0b
--- /dev/null
+++ b/code/nnv/examples/Submission/WiP_3d/verify_vessel_gpu.m
@@ -0,0 +1,82 @@
+%% Verify vessel dataset
+% vesselMNIST3D, input size: 28x28x28
+
+% Data
+dataset = "../../../../../data/medmnist/mat_files/vesselmnist3d.mat"; % path to data
+modelpath = "../../../../../data/medmnist/models/model_vesselmnist3d.mat";
+
+disp("Begin verification of vessel3d");
+
+% Load data
+load(dataset);
+
+% data to verify (test set)
+test_images = permute(test_images, [2 3 4 5 1]);
+test_labels = test_labels + 1;
+
+% load network
+load(modelpath);
+matlabNet = net;
+net = matlab2nnv(net);
+
+% select volumes to verify
+N = 50;
+idxs = zeros(N,1);
+count = 1;
+
+for i = 1:length(test_labels)
+    y = classify(matlabNet,test_images(:,:,:,i));
+    if single(y) == test_labels(i)
+        idxs(count) = i;
+        count = count + 1;
+    end
+    if count > N
+        break
+    end
+end
+
+inputs = single(test_images(:,:,:,idxs));
+targets = single(test_labels(idxs));
+
+% Reachability parameters
+reachOptions = struct;
+reachOptions.reachMethod = 'relax-star-area';
+reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
+reachOptions.device = 'gpu';
+
+
+% Study variables
+advType = ["add", "remove"];
+maxpixels = [50, 100, 500, 1000]; %out of 28x28x28 pixels
+epsilon = 1; % ep / 255
+
+
+%% Verification analysis
+for a=advType
+    for mp=maxpixels
+        for ep=epsilon
+            
+            % 1) Initialize results var
+            results = zeros(N,2);
+            
+            % 2) Create adversarial attack
+            adv_attack = struct;
+            adv_attack.Name = a; % add or remove
+            adv_attack.max_pixels = mp; % Max number of pixels to modify from input image
+            adv_attack.noise_de = ep/255; % disturbance (noise) on pixels
+            
+            % 3) Begin verification analysis
+            for i=1:N
+                img = inputs(:,:,:,i);
+                target = targets(i);
+                results(i,:) = verify_instance_shape(net, img, target, adv_attack, reachOptions);
+            end
+            
+            % 4) % save results
+            save("resultsGPU/verification_vessel_"+ a +"_" + ep +"_" + mp + ".mat", "results");
+
+        end
+    end
+end
+
diff --git a/code/nnv/tests/set/image_star/test_ImageStar_getRange.m b/code/nnv/tests/set/image_star/test_ImageStar_getRange.m
index 94c2955e85..90a88db6fb 100644
--- a/code/nnv/tests/set/image_star/test_ImageStar_getRange.m
+++ b/code/nnv/tests/set/image_star/test_ImageStar_getRange.m
@@ -11,9 +11,53 @@
 UB(:,:,2) = [0.1 0.15 0 0; 0 0 0 0; 0 0 0 0; 0 0 0 0];
 UB(:,:,3) = UB(:,:,2);
 
+%% 1) Get Range
 image = ImageStar(IM, LB, UB);
-tic;
 [xmin, xmax] = image.getRange(1,1,1);
-toc;
 display(xmin);
-display(xmax);
\ No newline at end of file
+display(xmax);
+
+%% 2) Get Ranges
+image = ImageStar(IM, LB, UB);
+[xmin, xmax] = image.getRanges;
+
+%% 3) Estimate Ranges
+image = ImageStar(IM, LB, UB);
+[xmin, xmax] = image.estimateRanges;
+
+%% 4) Compare ranges (estimate >= get)
+image1 = ImageStar(IM, LB, UB);
+t = tic;
+[xmin1, xmax1] = image1.estimateRanges;
+t1 = toc(t);
+
+% estimate ranges should be faster, but an overapproximation of getRanges
+image2 = ImageStar(IM, LB, UB);
+t = tic;
+[xmin2, xmax2] = image2.getRanges;
+t2 = toc(t);
+
+disp("Estimate took " + string(t1) +" seconds vs getRanges, that run on " +string(t2) +"seconds");
+
+assert(all(xmin1 - xmin2 <= eps, 'all'));
+assert(all(xmax1 - xmax2 >= -eps, 'all'));
+
+%% 5) Test from issues
+
+V(1,1,1,1) = 0;
+V(1,1,1,2) = -1;
+V(1,1,1,3) = 1;
+C = [0 0];
+d = 0;
+ub = [1; 1];
+lb = -ub;
+
+I1 = ImageStar(V, C, d, lb, ub);
+I2 = ImageStar(V, C, d, lb, ub);
+
+[xmin1, xmax1] = I1.estimateRanges;
+[xmin2, xmax2] = I2.getRanges;
+
+
+assert(all(xmin1 - xmin2 <= eps, 'all'));
+assert(all(xmax1 - xmax2 >= -eps, 'all'));
\ No newline at end of file